WorldWideScience

Sample records for rank resources based

  1. Econophysics of a ranked demand and supply resource allocation problem

    Science.gov (United States)

    Priel, Avner; Tamir, Boaz

    2018-01-01

    We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

  2. Ranking agricultural, environmental and natural resource economics journals: A note

    OpenAIRE

    Halkos, George; Tzeremes, Nickolaos

    2012-01-01

    This paper by applying Data Envelopment Analysis (DEA) ranks for the first time Economics journals in the field of Agricultural, Environmental and Natural Resource. Specifically, by using one composite input and one composite output the paper ranks 32 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with t...

  3. Low-rank coal study : national needs for resource development. Volume 2. Resource characterization

    Energy Technology Data Exchange (ETDEWEB)

    1980-11-01

    Comprehensive data are presented on the quantity, quality, and distribution of low-rank coal (subbituminous and lignite) deposits in the United States. The major lignite-bearing areas are the Fort Union Region and the Gulf Lignite Region, with the predominant strippable reserves being in the states of North Dakota, Montana, and Texas. The largest subbituminous coal deposits are in the Powder River Region of Montana and Wyoming, The San Juan Basin of New Mexico, and in Northern Alaska. For each of the low-rank coal-bearing regions, descriptions are provided of the geology; strippable reserves; active and planned mines; classification of identified resources by depth, seam thickness, sulfur content, and ash content; overburden characteristics; aquifers; and coal properties and characteristics. Low-rank coals are distinguished from bituminous coals by unique chemical and physical properties that affect their behavior in extraction, utilization, or conversion processes. The most characteristic properties of the organic fraction of low-rank coals are the high inherent moisture and oxygen contents, and the correspondingly low heating value. Mineral matter (ash) contents and compositions of all coals are highly variable; however, low-rank coals tend to have a higher proportion of the alkali components CaO, MgO, and Na/sub 2/O. About 90% of the reserve base of US low-rank coal has less than one percent sulfur. Water resources in the major low-rank coal-bearing regions tend to have highly seasonal availabilities. Some areas appear to have ample water resources to support major new coal projects; in other areas such as Texas, water supplies may be constraining factor on development.

  4. Citation graph based ranking in Invenio

    CERN Document Server

    Marian, Ludmila; Rajman, Martin; Vesely, Martin

    2010-01-01

    Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

  5. SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

    Science.gov (United States)

    Shams, Bita; Haratizadeh, Saman

    2016-09-01

    Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

  6. Iris Template Protection Based on Local Ranking

    Directory of Open Access Journals (Sweden)

    Dongdong Zhao

    2018-01-01

    Full Text Available Biometrics have been widely studied in recent years, and they are increasingly employed in real-world applications. Meanwhile, a number of potential threats to the privacy of biometric data arise. Iris template protection demands that the privacy of iris data should be protected when performing iris recognition. According to the international standard ISO/IEC 24745, iris template protection should satisfy the irreversibility, revocability, and unlinkability. However, existing works about iris template protection demonstrate that it is difficult to satisfy the three privacy requirements simultaneously while supporting effective iris recognition. In this paper, we propose an iris template protection method based on local ranking. Specifically, the iris data are first XORed (Exclusive OR operation with an application-specific string; next, we divide the results into blocks and then partition the blocks into groups. The blocks in each group are ranked according to their decimal values, and original blocks are transformed to their rank values for storage. We also extend the basic method to support the shifting strategy and masking strategy, which are two important strategies for iris recognition. We demonstrate that the proposed method satisfies the irreversibility, revocability, and unlinkability. Experimental results on typical iris datasets (i.e., CASIA-IrisV3-Interval, CASIA-IrisV4-Lamp, UBIRIS-V1-S1, and MMU-V1 show that the proposed method could maintain the recognition performance while protecting the privacy of iris data.

  7. Fuzzy-set based contingency ranking

    International Nuclear Information System (INIS)

    Hsu, Y.Y.; Kuo, H.C.

    1992-01-01

    In this paper, a new approach based on fuzzy set theory is developed for contingency ranking of Taiwan power system. To examine whether a power system can remain in a secure and reliable operating state under contingency conditions, those contingency cases that will result in loss-of-load, loss-of generation, or islanding are first identified. Then 1P-1Q iteration of fast decoupled load flow is preformed to estimate post-contingent quantities (line flows, bus voltages) for other contingency cases. Based on system operators' past experience, each post-contingent quantity is assigned a degree of severity according to the potential damage that could be imposed on the power system by the quantity, should the contingency occurs. An approach based on fuzzy set theory is developed to deal with the imprecision of linguistic terms

  8. Evaluation and Ranking of Geothermal Resources for Electrical Generation or Electrical Offset in Idaho, Montana, Oregon and Washington. Volume I.

    Energy Technology Data Exchange (ETDEWEB)

    Bloomquist, R. Gordon

    1985-06-01

    The objective was to consolidate and evaluate all geologic, environmental, and legal and institutional information in existing records and files, and to apply a uniform methodology to the evaluation and ranking of sites to allow the making of creditable forecasts of the supply of geothermal energy which could be available in the region over a 20 year planning horizon. A total of 1265 potential geothermal resource sites were identified from existing literature. Site selection was based upon the presence of thermal and mineral springs or wells and/or areas of recent volcanic activity and high heat flow. 250 sites were selected for detailed analysis. A methodology to rank the sites by energy potential, degree of developability, and cost of energy was developed. Resource developability was ranked by a method based on a weighted variable evaluation of resource favorability. Sites were ranked using an integration of values determined through the cost and developability analysis. 75 figs., 63 tabs.

  9. Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models

    NARCIS (Netherlands)

    Hallin, M.; van den Akker, R.; Werker, B.J.M.

    2012-01-01

    Abstract: This paper introduces rank-based tests for the cointegrating rank in an Error Correction Model with i.i.d. elliptical innovations. The tests are asymptotically distribution-free, and their validity does not depend on the actual distribution of the innovations. This result holds despite the

  10. Ranking the Online Documents Based on Relative Credibility Measures

    Directory of Open Access Journals (Sweden)

    Ahmad Dahlan

    2013-09-01

    Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

  11. Ranking the Online Documents Based on Relative Credibility Measures

    Directory of Open Access Journals (Sweden)

    Ahmad Dahlan

    2009-05-01

    Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

  12. Individual Preference Rankings Compatible with Prices, Income Distributions and Total Resources

    DEFF Research Database (Denmark)

    Balasko, Yves; Tvede, Mich

    We consider the problem of determining the individual preference rankings that are necessarily implied by a dataset consisting of prices, income distributions and total resources. We show the equivalence between the compatibility with individual preference rankings and the existence of a solution...

  13. Quantum probability ranking principle for ligand-based virtual screening

    Science.gov (United States)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  14. Quantum probability ranking principle for ligand-based virtual screening.

    Science.gov (United States)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  15. A Citation-Based Ranking of Strategic Management Journals

    OpenAIRE

    Azar, Ofer H.; Brock, David M.

    2007-01-01

    Rankings of strategy journals are important for authors, readers, and promotion and tenure committees. We present several rankings, based either on the number of articles that cited the journal or the per-article impact. Our analyses cover various periods between 1991 and 2006, for most of which the Strategic Management Journal was in first place and Journal of Economics & Management Strategy (JEMS) second, although JEMS ranked first in certain instances. Long Range Planning and Technology An...

  16. CNN-based ranking for biomedical entity normalization.

    Science.gov (United States)

    Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

    2017-10-03

    Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

  17. A Case-Based Reasoning Method with Rank Aggregation

    Science.gov (United States)

    Sun, Jinhua; Du, Jiao; Hu, Jian

    2018-03-01

    In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

  18. A Semi-Preemptive Computational Service System with Limited Resources and Dynamic Resource Ranking

    Directory of Open Access Journals (Sweden)

    Fang-Yie Leu

    2012-03-01

    Full Text Available In this paper, we integrate a grid system and a wireless network to present a convenient computational service system, called the Semi-Preemptive Computational Service system (SePCS for short, which provides users with a wireless access environment and through which a user can share his/her resources with others. In the SePCS, each node is dynamically given a score based on its CPU level, available memory size, current length of waiting queue, CPU utilization and bandwidth. With the scores, resource nodes are classified into three levels. User requests based on their time constraints are also classified into three types. Resources of higher levels are allocated to more tightly constrained requests so as to increase the total performance of the system. To achieve this, a resource broker with the Semi-Preemptive Algorithm (SPA is also proposed. When the resource broker cannot find suitable resources for the requests of higher type, it preempts the resource that is now executing a lower type request so that the request of higher type can be executed immediately. The SePCS can be applied to a Vehicular Ad Hoc Network (VANET, users of which can then exploit the convenient mobile network services and the wireless distributed computing. As a result, the performance of the system is higher than that of the tested schemes.

  19. INTEL: Intel based systems move up in supercomputing ranks

    CERN Multimedia

    2002-01-01

    "The TOP500 supercomputer rankings released today at the Supercomputing 2002 conference show a dramatic increase in the number of Intel-based systems being deployed in high-performance computing (HPC) or supercomputing areas" (1/2 page).

  20. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    International Nuclear Information System (INIS)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

  1. A network-based dynamical ranking system for competitive sports

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-12-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  2. Ranking of Developing Countries Based on the Economic Freedom Index

    OpenAIRE

    Zirak, Masoumeh; Mehrara, Mohsen

    2013-01-01

    In this paper we’ve ranked developing countries based on the Economic Freedom index. Therefore we are trying to do the analysis how this ranking is done using numerical taxonomic methodology. To do this, by estimating the effects of the determinants of FDI in 123 developing countries from 1997 to 2010, results showed that with regard to the degree of economic freedom or Economic openness, attract foreign direct investment in each country is different. In this study china, Equator, Liberia, Az...

  3. Faculty Challenges across Rank in Liberal Arts Colleges: A Human Resources Perspective

    Science.gov (United States)

    Baker, Vicki L.; Pifer, Meghan J.; Lunsford, Laura G.

    2016-01-01

    This article focuses on the challenges faced by faculty members in a consortium of 13 Liberal Arts Colleges (LACs). We present findings, by academic rank, from a mixed-methods study of faculty development needs and experiences within the consortium. Relying on human resource principles, we advocate a greater focus on the development of the person,…

  4. Image Re-Ranking Based on Topic Diversity.

    Science.gov (United States)

    Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

    2017-08-01

    Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

  5. Content-based image retrieval with ontological ranking

    Science.gov (United States)

    Tsai, Shen-Fu; Tsai, Min-Hsuan; Huang, Thomas S.

    2010-02-01

    Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text; the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well; second, the grouping

  6. International Conference on Robust Rank-Based and Nonparametric Methods

    CERN Document Server

    McKean, Joseph

    2016-01-01

    The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with r...

  7. Strategic Entrepreneurship Based Model of Catch-up University in Global Rankings

    Directory of Open Access Journals (Sweden)

    Kozlov Mikhail

    2016-01-01

    Full Text Available The paper will help answer the question, why only few universities managed to succeed significantly in their global ranking advancement, while most of their competitors fail. For this purpose it will introduce a new strategically entrepreneurial catch-up university framework, based on the combination of the resource based view, dynamic capabilities, strategic entrepreneurship and latecomer organization concepts. The new framework logics explains the advantages of being ambidextrous for ranking oriented universities and pursuing new potentially more favorable opportunities for research development. It will propose that substantial increase in the level of dynamic capabilities of the universities and their resource base accumulation is based on the use of the new combination of financial, human and social capital combined with strategic management of these resources in the process of identification and exploitation of greater opportunities.

  8. Logic-based aggregation methods for ranking student applicants

    Directory of Open Access Journals (Sweden)

    Milošević Pavle

    2017-01-01

    Full Text Available In this paper, we present logic-based aggregation models used for ranking student applicants and we compare them with a number of existing aggregation methods, each more complex than the previous one. The proposed models aim to include depen- dencies in the data using Logical aggregation (LA. LA is a aggregation method based on interpolative Boolean algebra (IBA, a consistent multi-valued realization of Boolean algebra. This technique is used for a Boolean consistent aggregation of attributes that are logically dependent. The comparison is performed in the case of student applicants for master programs at the University of Belgrade. We have shown that LA has some advantages over other presented aggregation methods. The software realization of all applied aggregation methods is also provided. This paper may be of interest not only for student ranking, but also for similar problems of ranking people e.g. employees, team members, etc.

  9. Ranking Scientific Publications Based on Their Citation Graph

    CERN Document Server

    Marian, L; Rajman, M

    2009-01-01

    CDS Invenio is the web-based integrated digital library system developed at CERN. It is a suite of applications which provides the framework and tools for building and managing an autonomous digital library server. Within this framework, the goal of this project is to implement new ranking methods based on the bibliographic citation graph extracted from the CDS Invenio database. As a first step, we implemented the Citation Count as a baseline ranking method. The major disadvantage of this method is that all citations are treated equally, disregarding their importance and their publication date. To overcome this drawback, we consider two different approaches: a link-based approach which extends the PageRank model to the bibliographic citation graph and a time-dependent approach which takes into account time in the citation counts. In addition, we also combined these two approaches in a hybrid model based on a time-dependent PageRank. In the present document, we describe the conceptual background behind our new...

  10. Result diversification based on query-specific cluster ranking

    NARCIS (Netherlands)

    He, J.; Meij, E.; de Rijke, M.

    2011-01-01

    Result diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking, in which diversification

  11. Result Diversification Based on Query-Specific Cluster Ranking

    NARCIS (Netherlands)

    J. He (Jiyin); E. Meij; M. de Rijke (Maarten)

    2011-01-01

    htmlabstractResult diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking,

  12. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...

  13. Ranking Institutional Settings Based on Publications in Community Psychology Journals

    Science.gov (United States)

    Jason, Leonard A.; Pokorny, Steven B.; Patka, Mazna; Adams, Monica; Morello, Taylor

    2007-01-01

    Two primary outlets for community psychology research, the "American Journal of Community Psychology" and the "Journal of Community Psychology", were assessed to rank institutions based on publication frequency and scientific influence of publications over a 32-year period. Three specific periods were assessed (1973-1983, 1984-1994, 1995-2004).…

  14. Evaluation and Ranking of Geothermal Resources for Electrical Generation or Electrical Offset in Idaho, Montana, Oregon and Washington. Volume II.

    Energy Technology Data Exchange (ETDEWEB)

    Bloomquist, R. Gordon

    1985-06-01

    This volume contains appendices on: (1) resource assessment - electrical generation computer results; (2) resource assessment summary - direct use computer results; (3) electrical generation (high temperature) resource assessment computer program listing; (4) direct utilization (low temperature) resource assessment computer program listing; (5) electrical generation computer program CENTPLANT and related documentation; (6) electrical generation computer program WELLHEAD and related documentation; (7) direct utilization computer program HEATPLAN and related documentation; (8) electrical generation ranking computer program GEORANK and related documentation; (9) direct utilization ranking computer program GEORANK and related documentation; and (10) life cycle cost analysis computer program and related documentation. (ACR)

  15. Lunar resource base

    Science.gov (United States)

    Pulley, John; Wise, Todd K.; Roy, Claude; Richter, Phil

    A lunar base that exploits local resources to enhance the productivity of a total SEI scenario is discussed. The goals were to emphasize lunar science and to land men on Mars in 2016 using significant amounts of lunar resources. It was assumed that propulsion was chemical and the surface power was non-nuclear. Three phases of the base build-up are outlined, the robotic emplacement of the first elements is detailed and a discussion of future options is included.

  16. Variable screening and ranking using sampling-based sensitivity measures

    International Nuclear Information System (INIS)

    Wu, Y-T.; Mohanty, Sitakanta

    2006-01-01

    This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

  17. An adaptive ES with a ranking based constraint handling strategy

    Directory of Open Access Journals (Sweden)

    Kusakci Ali Osman

    2014-01-01

    Full Text Available To solve a constrained optimization problem, equality constraints can be used to eliminate a problem variable. If it is not feasible, the relations imposed implicitly by the constraints can still be exploited. Most conventional constraint handling methods in Evolutionary Algorithms (EAs do not consider the correlations between problem variables imposed by the constraints. This paper relies on the idea that a proper search operator, which captures mentioned implicit correlations, can improve performance of evolutionary constrained optimization algorithms. To realize this, an Evolution Strategy (ES along with a simplified Covariance Matrix Adaptation (CMA based mutation operator is used with a ranking based constraint-handling method. The proposed algorithm is tested on 13 benchmark problems as well as on a real life design problem. The outperformance of the algorithm is significant when compared with conventional ES-based methods.

  18. Nanotechnology strength indicators: international rankings based on US patents

    Science.gov (United States)

    Marinova, Dora; McAleer, Michael

    2003-01-01

    Technological strength indicators (TSIs) based on patent statistics for 1975-2000 are used to analyse patenting of nanotechnology in the USA, and to compile international rankings for the top 12 foreign patenting countries (namely Australia, Canada, France, Germany, Great Britain, Italy, Japan, Korea, the Netherlands, Sweden, Switzerland and Taiwan). As the indicators are not directly observable, various proxy variables are used, namely the technological specialization index for national priorities, patent shares for international presence, citation rate for the contribution of patents to knowledge development and rate of assigned patents for potential commercial benefits. The best performing country is France, followed by Japan and Canada. It is shown that expertise and strength in nanotechnology are not evenly distributed among the technologically advanced countries, with the TSIs revealing different emphases in the development of nanotechnology.

  19. A model-based approach to operational event groups ranking

    Energy Technology Data Exchange (ETDEWEB)

    Simic, Zdenko [European Commission Joint Research Centre, Petten (Netherlands). Inst. for Energy and Transport; Maqua, Michael [Gesellschaft fuer Anlagen- und Reaktorsicherheit mbH (GRS), Koeln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-Roses (France)

    2014-04-15

    The operational experience (OE) feedback provides improvements in all industrial activities. Identification of the most important and valuable groups of events within accumulated experience is important in order to focus on a detailed investigation of events. The paper describes the new ranking method and compares it with three others. Methods have been described and applied to OE events utilised by nuclear power plants in France and Germany for twenty years. The results show that different ranking methods only roughly agree on which of the event groups are the most important ones. In the new ranking method the analytical hierarchy process is applied in order to assure consistent and comprehensive weighting determination for ranking indexes. The proposed method allows a transparent and flexible event groups ranking and identification of the most important OE for further more detailed investigation in order to complete the feedback. (orig.)

  20. On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example.

    Science.gov (United States)

    Sailaukhanuly, Yerbolat; Zhakupbekova, Arai; Amutova, Farida; Carlsen, Lars

    2013-01-01

    Knowledge of the environmental behavior of chemicals is a fundamental part of the risk assessment process. The present paper discusses various methods of ranking of a series of persistent organic pollutants (POPs) according to the persistence, bioaccumulation and toxicity (PBT) characteristics. Traditionally ranking has been done as an absolute (total) ranking applying various multicriteria data analysis methods like simple additive ranking (SAR) or various utility functions (UFs) based rankings. An attractive alternative to these ranking methodologies appears to be partial order ranking (POR). The present paper compares different ranking methods like SAR, UF and POR. Significant discrepancies between the rankings are noted and it is concluded that partial order ranking, as a method without any pre-assumptions concerning possible relation between the single parameters, appears as the most attractive ranking methodology. In addition to the initial ranking partial order methodology offers a wide variety of analytical tools to elucidate the interplay between the objects to be ranked and the ranking parameters. In the present study is included an analysis of the relative importance of the single P, B and T parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Distant Supervision for Relation Extraction with Ranking-Based Methods

    Directory of Open Access Journals (Sweden)

    Yang Xiang

    2016-05-01

    Full Text Available Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion. However, distant supervision is still greatly limited by the quality of training data, due to its natural motivation for greatly reducing the heavy cost of data annotation. In this paper, we construct an architecture called MIML-sort (Multi-instance Multi-label Learning with Sorting Strategies, which is built on the famous MIML framework. Based on MIML-sort, we propose three ranking-based methods for sample selection with which we identify relation extractors from a subset of the training data. Experiments are set up on the KBP (Knowledge Base Propagation corpus, one of the benchmark datasets for distant supervision, which is large and noisy. Compared with previous work, the proposed methods produce considerably better results. Furthermore, the three methods together achieve the best F1 on the official testing set, with an optimal enhancement of F1 from 27.3% to 29.98%.

  2. Manifold Based Low-rank Regularization for Image Restoration and Semi-supervised Learning

    OpenAIRE

    Lai, Rongjie; Li, Jia

    2017-01-01

    Low-rank structures play important role in recent advances of many problems in image science and data science. As a natural extension of low-rank structures for data with nonlinear structures, the concept of the low-dimensional manifold structure has been considered in many data processing problems. Inspired by this concept, we consider a manifold based low-rank regularization as a linear approximation of manifold dimension. This regularization is less restricted than the global low-rank regu...

  3. A web-based tool for ranking landslide mitigation measures

    Science.gov (United States)

    Lacasse, S.; Vaciago, G.; Choi, Y. J.; Kalsnes, B.

    2012-04-01

    brief description, guidance on design, schematic details, practical examples and references for each mitigation measure. Each of the measures was given a score on its ability and applicability for different types of landslides and boundary conditions, and a decision support matrix was established. The web-based toolbox organizes the information in the compendium and provides an algorithm to rank the measures on the basis of the decision support matrix, and on the basis of the risk level estimated at the site. The toolbox includes a description of the case under study and offers a simplified option for estimating the hazard and risk levels of the slide at hand. The user selects the mitigation measures to be included in the assessment. The toolbox then ranks, with built-in assessment factors and weights and/or with user-defined ranking values and criteria, the mitigation measures included in the analysis. The toolbox includes data management, e.g. saving data half-way in an analysis, returning to an earlier case, looking up prepared examples or looking up information on mitigation measures. The toolbox also generates a report and has user-forum and help features. The presentation will give an overview of the mitigation measures considered and examples of the use of the toolbox, and will take the attendees through the application of the toolbox.

  4. Critical review of methods for risk ranking of food related hazards, based on risks for human health

    DEFF Research Database (Denmark)

    van der Fels-Klerx, H. J.; van Asselt, E. D.; Raley, M.

    2018-01-01

    This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science......, and the risk ranking method characterized. The methods were then clustered - based on their characteristics - into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years, multi......-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking...

  5. A stable systemic risk ranking in China's banking sector: Based on principal component analysis

    Science.gov (United States)

    Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

    2018-02-01

    In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

  6. Hyper-local, directions-based ranking of places

    DEFF Research Database (Denmark)

    Venetis, Petros; Gonzalez, Hector; Jensen, Christian S.

    2011-01-01

    they are numerous and contain precise locations. Specifically, the paper proposes a framework that takes a user location and a collection of near-by places as arguments, producing a ranking of the places. The framework enables a range of aspects of directions queries to be exploited for the ranking of places......, including the frequency with which places have been referred to in directions queries. Next, the paper proposes an algorithm and accompanying data structures capable of ranking places in response to hyper-local web queries. Finally, an empirical study with very large directions query logs offers insight...... into the potential of directions queries for the ranking of places and suggests that the proposed algorithm is suitable for use in real web search engines....

  7. Personalized Profile Based Search Interface With Ranked and Clustered Display

    National Research Council Canada - National Science Library

    Kumar, Sachin; Oztekin, B. U; Ertoz, Levent; Singhal, Saurabh; Han, Euihong; Kumar, Vipin

    2001-01-01

    We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list...

  8. Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

    Science.gov (United States)

    Tian, Yuling; Zhang, Hongxian

    2016-01-01

    For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

  9. A rank-based Prediction Algorithm of Learning User's Intention

    Science.gov (United States)

    Shen, Jie; Gao, Ying; Chen, Cang; Gong, HaiPing

    Internet search has become an important part in people's daily life. People can find many types of information to meet different needs through search engines on the Internet. There are two issues for the current search engines: first, the users should predetermine the types of information they want and then change to the appropriate types of search engine interfaces. Second, most search engines can support multiple kinds of search functions, each function has its own separate search interface. While users need different types of information, they must switch between different interfaces. In practice, most queries are corresponding to various types of information results. These queries can search the relevant results in various search engines, such as query "Palace" contains the websites about the introduction of the National Palace Museum, blog, Wikipedia, some pictures and video information. This paper presents a new aggregative algorithm for all kinds of search results. It can filter and sort the search results by learning three aspects about the query words, search results and search history logs to achieve the purpose of detecting user's intention. Experiments demonstrate that this rank-based method for multi-types of search results is effective. It can meet the user's search needs well, enhance user's satisfaction, provide an effective and rational model for optimizing search engines and improve user's search experience.

  10. A novel three-stage distance-based consensus ranking method

    Science.gov (United States)

    Aghayi, Nazila; Tavana, Madjid

    2018-05-01

    In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

  11. Rank-based model selection for multiple ions quantum tomography

    International Nuclear Information System (INIS)

    Guţă, Mădălin; Kypraios, Theodore; Dryden, Ian

    2012-01-01

    The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the ‘sparsity’ properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods—the Akaike information criterion (AIC) and the Bayesian information criterion (BIC)—two models consisting of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of four ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a four ions experiment aimed at creating a Smolin state of rank 4. By applying the two methods together with the Pearson χ 2 test we conclude that the data can be suitably described with a model whose rank is between 7 and 9. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements. (paper)

  12. How Should Journal Quality be Ranked? An Application to Agricultural, Energy, Environment and Resource Economics

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael)

    2011-01-01

    textabstractExperts possess knowledge and information that are not publicly available. The paper is concerned with the ranking of academic journal quality and research impact using a survey of experts from a national project on ranking academic finance journals. A comparison is made with publicly

  13. A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model

    Directory of Open Access Journals (Sweden)

    Madjid Tavana

    2007-01-01

    Full Text Available Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM. The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983 and Cook and Kress (1985 into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962 and the two methods proposed by Beck and Lin (1983 and Cook and Kress (1985. DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.

  14. Ranking of healthcare programmes based on health outcome, health costs and safe delivery of care in hospital pharmacy practice.

    Science.gov (United States)

    Brisseau, Lionel; Bussières, Jean-François; Bois, Denis; Vallée, Marc; Racine, Marie-Claude; Bonnici, André

    2013-02-01

    To establish a consensual and coherent ranking of healthcare programmes that involve the presence of ward-based and clinic-based clinical pharmacists, based on health outcome, health costs and safe delivery of care. This descriptive study was derived from a structured dialogue (Delphi technique) among directors of pharmacy department. We established a quantitative profile of healthcare programmes at five sites that involved the provision of ward-based and clinic-based pharmaceutical care. A summary table of evidence established a unique quality rating per inpatient (clinic-based) or outpatient (ward-based) healthcare programme. Each director rated the perceived impact of pharmaceutical care per inpatient or outpatient healthcare programme on three fields: health outcome, health costs and safe delivery of care. They agreed by consensus on the final ranking of healthcare programmes. A ranking was assigned for each of the 18 healthcare programmes for outpatient care and the 17 healthcare programmes for inpatient care involving the presence of pharmacists, based on health outcome, health costs and safe delivery of care. There was a good correlation between ranking based on data from a 2007-2008 Canadian report on hospital pharmacy practice and the ranking proposed by directors of pharmacy department. Given the often limited human and financial resources, managers should consider the best evidence available on a profession's impact to plan healthcare services within an organization. Data are few on ranking healthcare programmes in order to prioritize which healthcare programme would mostly benefit from the delivery of pharmaceutical care by ward-based and clinic-based pharmacists. © 2012 The Authors. IJPP © 2012 Royal Pharmaceutical Society.

  15. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

    Science.gov (United States)

    Chen, Jinying; Yu, Hong

    2017-04-01

    Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them. Targeted education can then be developed to improve patient EHR comprehension and the quality of care. The aim of this work was to develop FIT (Finding Important Terms for patients), an unsupervised natural language processing (NLP) system that ranks medical terms in EHR notes based on their importance to patients. We built FIT on a new unsupervised ensemble ranking model derived from the biased random walk algorithm to combine heterogeneous information resources for ranking candidate terms from each EHR note. Specifically, FIT integrates four single views (rankers) for term importance: patient use of medical concepts, document-level term salience, word co-occurrence based term relatedness, and topic coherence. It also incorporates partial information of term importance as conveyed by terms' unfamiliarity levels and semantic types. We evaluated FIT on 90 expert-annotated EHR notes and used the four single-view rankers as baselines. In addition, we implemented three benchmark unsupervised ensemble ranking methods as strong baselines. FIT achieved 0.885 AUC-ROC for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FIT for identifying important terms from EHR notes was 0.813 AUC-ROC. Both performance scores significantly exceeded the corresponding scores from the four single rankers (P<0.001). FIT also outperformed the three ensemble rankers for most metrics. Its performance is relatively insensitive to its parameter. FIT can automatically identify EHR terms important to patients. It may help develop future interventions

  16. Bibliometric Rankings of Journals Based on the Thomson Reuters Citations Database

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael)

    2015-01-01

    markdownabstract__Abstract__ Virtually all rankings of journals are based on citations, including self citations by journals and individual academics. The gold standard for bibliometric rankings based on citations data is the widely-used Thomson Reuters Web of Science (2014) citations database,

  17. Bibliometric Rankings of Journals based on the Thomson Reuters Citations Database

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael)

    2015-01-01

    markdownabstract__Abstract__ Virtually all rankings of journals are based on citations, including self citations by journals and individual academics. The gold standard for bibliometric rankings based on citations data is the widely-used Thomson Reuters Web of Science (2014) citations database,

  18. Semiparametric Gaussian copula models : Geometry and efficient rank-based estimation

    NARCIS (Netherlands)

    Segers, J.; van den Akker, R.; Werker, B.J.M.

    2014-01-01

    We propose, for multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically efficient estimator for the Euclidean copula parameter. This estimator is defined as a one-step update of a rank-based pilot estimator in the direction of

  19. Considerations when ranking stochastically modeled oil sands resource models for mining applications

    Energy Technology Data Exchange (ETDEWEB)

    Etris, E.L. [Society of Petroleum Engineers, Canadian Section, Calgary, AB (Canada)]|[Petro-Canada, Calgary, AB (Canada); Idris, Y.; Hunter, A.C. [Petro-Canada, Calgary, AB (Canada)

    2008-10-15

    Alberta's Athabasca oil sands deposit has been targeted as a major resource for development. Bitumen recovery operations fall into 2 categories, namely mining and in situ operations. Mining recovery is done above ground level and consists of open pit digging, disaggregation of the bitumen-saturated sediment through crushing followed by pipeline transport in a water-based slurry and then separation of oil, water and sediment. In situ recovery consists of drilling wells and stimulating the oil sands in the subsurface with a thermal treatment to reduce the viscosity of the bitumen and allow it to come to the surface. Steam assisted gravity drainage (SAGD) is the most popular thermal treatment currently in use. Resource models that simulate the recovery process are needed for both mining and in situ recovery operations. Both types can benefit from the advantages of a stochastic modeling process for resource model building and uncertainty evaluation. Stochastic modeling provides a realistic geology and allows for multiple realizations, which mining operations can use to evaluate the variability of recoverable bitumen volumes and develop mine plans accordingly. This paper described the processes of stochastic modelling and of determining the appropriate single realization for mine planning as applied to the Fort Hills oil sands mine which is currently in the early planning stage. The modeling exercise was used to estimate the in-place resource and quantify the uncertainty in resource volumes. The stochastic models were checked against those generated from conventional methods to identify any differences and to make the appropriate adaptations. 13 refs., 3 tabs., 16 figs.

  20. Low-rank coal study: national needs for resource development. Volume 3. Technology evaluation

    Energy Technology Data Exchange (ETDEWEB)

    1980-11-01

    Technologies applicable to the development and use of low-rank coals are analyzed in order to identify specific needs for research, development, and demonstration (RD and D). Major sections of the report address the following technologies: extraction; transportation; preparation, handling and storage; conventional combustion and environmental control technology; gasification; liquefaction; and pyrolysis. Each of these sections contains an introduction and summary of the key issues with regard to subbituminous coal and lignite; description of all relevant technology, both existing and under development; a description of related environmental control technology; an evaluation of the effects of low-rank coal properties on the technology; and summaries of current commercial status of the technology and/or current RD and D projects relevant to low-rank coals.

  1. Low-rank coal study: national needs for resource development. Volume 6. Peat

    Energy Technology Data Exchange (ETDEWEB)

    1980-11-01

    The requirements and potential for development of US peat resources for energy use are reviewed. Factors analyzed include the occurrence and properties of major peat deposits; technologies for extraction, dewatering, preparation, combustion, and conversion of peat to solid, liquid, or gaseous fuels; environmental, regulatory, and market constraints; and research, development, and demonstration (RD and D) needs. Based on a review of existing research efforts, recommendations are made for a comprehensive national RD and D program to enhance the use of peat as an energy source.

  2. Dominance-based ranking functions for interval-valued intuitionistic fuzzy sets.

    Science.gov (United States)

    Chen, Liang-Hsuan; Tu, Chien-Cheng

    2014-08-01

    The ranking of interval-valued intuitionistic fuzzy sets (IvIFSs) is difficult since they include the interval values of membership and nonmembership. This paper proposes ranking functions for IvIFSs based on the dominance concept. The proposed ranking functions consider the degree to which an IvIFS dominates and is not dominated by other IvIFSs. Based on the bivariate framework and the dominance concept, the functions incorporate not only the boundary values of membership and nonmembership, but also the relative relations among IvIFSs in comparisons. The dominance-based ranking functions include bipolar evaluations with a parameter that allows the decision-maker to reflect his actual attitude in allocating the various kinds of dominance. The relationship for two IvIFSs that satisfy the dual couple is defined based on four proposed ranking functions. Importantly, the proposed ranking functions can achieve a full ranking for all IvIFSs. Two examples are used to demonstrate the applicability and distinctiveness of the proposed ranking functions.

  3. GeoSearcher: Location-Based Ranking of Search Engine Results.

    Science.gov (United States)

    Watters, Carolyn; Amoudi, Ghada

    2003-01-01

    Discussion of Web queries with geospatial dimensions focuses on an algorithm that assigns location coordinates dynamically to Web sites based on the URL. Describes a prototype search system that uses the algorithm to re-rank search engine results for queries with a geospatial dimension, thus providing an alternative ranking order for search engine…

  4. Population based ranking of frameless CT-MRI registration methods

    Energy Technology Data Exchange (ETDEWEB)

    Opposits, Gabor; Kis, Sandor A.; Tron, Lajos; Emri, Miklos [Debrecen Univ. (Hungary). Dept. of Nuclear Medicine; Berenyi, Ervin [Debrecen Univ. (Hungary). Dept. of Biomedical Laboratory and Imaging Science; Takacs, Endre [Rotating Gamma Ltd., Debrecen (Hungary); Dobai, Jozsef G.; Bognar, Laszlo [Debrecen Univ., Medical Center (Hungary). Dept. of Neurosurgery; Szuecs, Bernadett [ScanoMed Ltd., Debrecen (Hungary)

    2015-07-01

    Clinical practice often requires simultaneous information obtained by two different imaging modalities. Registration algorithms are commonly used for this purpose. Automated procedures are very helpful in cases when the same kind of registration has to be performed on images of a high number of subjects. Radiotherapists would prefer to use the best automated method to assist therapy planning, however there are not accepted procedures for ranking the different registration algorithms. We were interested in developing a method to measure the population level performance of CT-MRI registration algorithms by a parameter of values in the [0,1] interval. Pairs of CT and MRI images were collected from 1051 subjects. Results of an automated registration were corrected manually until a radiologist and a neurosurgeon expert both accepted the result as good. This way 1051 registered MRI images were produced by the same pair of experts to be used as gold standards for the evaluation of the performance of other registration algorithms. Pearson correlation coefficient, mutual information, normalized mutual information, Kullback-Leibler divergence, L{sub 1} norm and square L{sub 2} norm (dis)similarity measures were tested for sensitivity to indicate the extent of (dis)similarity of a pair of individual mismatched images. The square Hellinger distance proved suitable to grade the performance of registration algorithms at population level providing the developers with a valuable tool to rank algorithms. The developed procedure provides an objective method to find the registration algorithm performing the best on the population level out of newly constructed or available preselected ones.

  5. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  6. Ranking Based Locality Sensitive Hashing Enabled Cancelable Biometrics: Index-of-Max Hashing

    OpenAIRE

    Jin, Zhe; Lai, Yen-Lung; Hwang, Jung-Yeon; Kim, Soohyung; Teoh, Andrew Beng Jin

    2017-01-01

    In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The disc...

  7. The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

    Science.gov (United States)

    Jaini, Nor I.; Utyuzhnikov, Sergei V.

    2017-08-01

    Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

  8. Spectral-based features ranking for gamelan instruments identification using filter techniques

    Directory of Open Access Journals (Sweden)

    Diah P Wulandari

    2013-03-01

    Full Text Available In this paper, we describe an approach of spectral-based features ranking for Javanese gamelaninstruments identification using filter techniques. The model extracted spectral-based features set of thesignal using Short Time Fourier Transform (STFT. The rank of the features was determined using the fivealgorithms; namely ReliefF, Chi-Squared, Information Gain, Gain Ratio, and Symmetric Uncertainty. Then,we tested the ranked features by cross validation using Support Vector Machine (SVM. The experimentshowed that Gain Ratio algorithm gave the best result, it yielded accuracy of 98.93%.

  9. Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM)

    International Nuclear Information System (INIS)

    Gao, Hao; Osher, Stanley; Yu, Hengyong; Wang, Ge

    2011-01-01

    We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations. (papers)

  10. Ranking of input parameters importance for BWR stability based on Ringhals-1

    International Nuclear Information System (INIS)

    Gajev, Ivan; Kozlowski, Tomasz; Xu, Yunlin; Downar, Thomas

    2011-01-01

    Unstable behavior of Boiling Water Reactors (BWRs) is known to occur during operation at certain power and flow conditions. Uncertainty calculations for BWR stability, based on the Wilks' formula, have been already done for the Ringhals-1 benchmark. In this work, these calculations have been used to identify and rank the most important parameters affecting the stability of the Ringhals-1 plant. The ranking has been done in two different ways and a comparison of these two methods has been demonstrated. Results show that the methods provide different, but meaningful evaluations of the ranking. (author)

  11. A Citation-Based Ranking of German-Speaking Researchers in Business Administration with Data of Google Scholar

    Science.gov (United States)

    Dilger, Alexander; Müller, Harry

    2013-01-01

    Rankings of academics can be constructed in two different ways, either based on journal rankings or based on citations. Although citation-based rankings promise some fundamental advantages they are still not common in German-speaking business administration. However, the choice of the underlying database is crucial. This article argues that for…

  12. Ranking of bank branches with undesirable and fuzzy data: A DEA-based approach

    Directory of Open Access Journals (Sweden)

    Sohrab Kordrostami

    2016-07-01

    Full Text Available Banks are one of the most important financial sectors in order to the economic development of each country. Certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. Sometimes the performance of banks must be measured in the presence of undesirable and vague factors. For these reasons in the current paper a procedure based on data envelopment analysis (DEA is introduced for evaluating the efficiency and complete ranking of decision making units (DMUs where undesirable and fuzzy measures exist. To illustrate, in the presence of undesirable and fuzzy measures, DMUs are evaluated by using a fuzzy expected value approach and DMUs with similar efficiency scores are ranked by using constraints and the Maximal Balance Index based on the optimal shadow prices. Afterwards, the efficiency scores of 25 branches of an Iranian commercial bank are evaluated using the proposed method. Also, a complete ranking of bank branches is presented to discriminate branches.

  13. Critical review of methods for risk ranking of food-related hazards, based on risks for human health.

    Science.gov (United States)

    Van der Fels-Klerx, H J; Van Asselt, E D; Raley, M; Poulsen, M; Korsgaard, H; Bredsdorff, L; Nauta, M; D'agostino, M; Coles, D; Marvin, H J P; Frewer, L J

    2018-01-22

    This study aimed to critically review methods for ranking risks related to food safety and dietary hazards on the basis of their anticipated human health impacts. A literature review was performed to identify and characterize methods for risk ranking from the fields of food, environmental science and socio-economic sciences. The review used a predefined search protocol, and covered the bibliographic databases Scopus, CAB Abstracts, Web of Sciences, and PubMed over the period 1993-2013. All references deemed relevant, on the basis of predefined evaluation criteria, were included in the review, and the risk ranking method characterized. The methods were then clustered-based on their characteristics-into eleven method categories. These categories included: risk assessment, comparative risk assessment, risk ratio method, scoring method, cost of illness, health adjusted life years (HALY), multi-criteria decision analysis, risk matrix, flow charts/decision trees, stated preference techniques and expert synthesis. Method categories were described by their characteristics, weaknesses and strengths, data resources, and fields of applications. It was concluded there is no single best method for risk ranking. The method to be used should be selected on the basis of risk manager/assessor requirements, data availability, and the characteristics of the method. Recommendations for future use and application are provided.

  14. Discovering urban mobility patterns with PageRank based traffic modeling and prediction

    Science.gov (United States)

    Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

    2017-11-01

    Urban transportation system can be viewed as complex network with time-varying traffic flows as links to connect adjacent regions as networked nodes. By computing urban traffic evolution on such temporal complex network with PageRank, it is found that for most regions, there exists a linear relation between the traffic congestion measure at present time and the PageRank value of the last time. Since the PageRank measure of a region does result from the mutual interactions of the whole network, it implies that the traffic state of a local region does not evolve independently but is affected by the evolution of the whole network. As a result, the PageRank values can act as signatures in predicting upcoming traffic congestions. We observe the aforementioned laws experimentally based on the trajectory data of 12000 taxies in Beijing city for one month.

  15. Individual preference rankings compatible with prices, income distributions and total resources

    DEFF Research Database (Denmark)

    Balasko, Yves; Tvede, Mich

    2010-01-01

    of Afriat's inequalities that characterize the rationalizability of a finite set of individual consumption data. Exploiting this structure, we also give new proofs of the rationalizability of finite data sets where total resources are close to being collinear and the contractibility and pathconnectedness...

  16. MCDM based evaluation and ranking of commercial off-the-shelf using fuzzy based matrix method

    Directory of Open Access Journals (Sweden)

    Rakesh Garg

    2017-04-01

    Full Text Available In today’s scenario, software has become an essential component in all kinds of systems. The size and the complexity of the software increases with a corresponding increase in its functionality, hence leads to the development of the modular software systems. Software developers emphasize on the concept of component based software engineering (CBSE for the development of modular software systems. The CBSE concept consists of dividing the software into a number of modules; selecting Commercial Off-the-Shelf (COTS for each module; and finally integrating the modules to develop the final software system. The selection of COTS for any module plays a vital role in software development. To address the problem of selection of COTS, a framework for ranking and selection of various COTS components for any software system based on expert opinion elicitation and fuzzy-based matrix methodology is proposed in this research paper. The selection problem is modeled as a multi-criteria decision making (MCDM problem. The evaluation criteria are identified through extensive literature study and the COTS components are ranked based on these identified and selected evaluation criteria using the proposed methods according to the value of a permanent function of their criteria matrices. The methodology is explained through an example and is validated by comparing with an existing method.

  17. The ranking of scientists based on scientific publications assessment.

    Science.gov (United States)

    Zerem, Enver

    2017-11-01

    It is generally accepted that the scientific impact factor (Web of Science) and the total number of citations of the articles published in a journal, are the most relevant parameters of the journal's significance. However, the significance of scientists is much more complicated to establish and the value of their scientific production cannot be directly reflected by the importance of the journals in which their articles are published. Evaluating the significance of scientists' accomplishments involves more complicated metrics than just their publication records. Based on a long term of academic experience, the author proposes objective criteria to estimate the scientific merit of an individual's publication record. This metric can serve as a pragmatic tool and the nidus for discussion within the readership of this journal. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    With the fast growth of Chinese economic,more and more capital will be invested in environmental projects.How to select the environmental investment projects(alternatives)for obtaining the best environmental quality and economic benefits is an important problem for the decision makers.The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria.A model for ranking the projects of municipal sewage treatment plants is proposed by using exports' information and the data of the real projects.And,the ranking result is given based on the PROMETHEE method. Furthermore,by means of the concept of the weight stability intervals(WSI),the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed.The result shows that some criteria,such as"proportion of benefit to projoct cost",will influence the ranking result of alternatives very strong while others not.The influence are not only from the value of criterion but also from the changing the weight of criterion.So,some criteria such as"proportion of benefit to projoct cost" are key critera for ranking the projects. Decision makers must be cautious to them.

  19. Social norms and rank-based nudging: Changing willingness to pay for healthy food.

    Science.gov (United States)

    Aldrovandi, Silvio; Brown, Gordon D A; Wood, Alex M

    2015-09-01

    People's evaluations in the domain of healthy eating are at least partly determined by the choice context. We systematically test reference level and rank-based models of relative comparisons against each other and explore their application to social norms nudging, an intervention that aims at influencing consumers' behavior by addressing their inaccurate beliefs about their consumption relative to the consumption of others. Study 1 finds that the rank of a product or behavior among others in the immediate comparison context, rather than its objective attributes, influences its evaluation. Study 2 finds that when a comparator is presented in isolation the same rank-based process occurs based on information retrieved from memory. Study 3 finds that telling people how their consumption ranks within a normative comparison sample increases willingness to pay for a healthy food by over 30% relative to the normal social norms intervention that tells them how they compare to the average. We conclude that social norms interventions should present rank information (e.g., "you are in the most unhealthy 10% of eaters") rather than information relative to the average (e.g., "you consume 500 calories more than the average person"). (c) 2015 APA, all rights reserved).

  20. Introducing trimming and function ranking to Solid Works based on function analysis

    NARCIS (Netherlands)

    Chechurin, Leonid S.; Wits, Wessel Willems; Bakker, Hans M.; Cascini, G.; Vaneker, Thomas H.J.

    2011-01-01

    TRIZ based Function Analysis models existing products based on functional interactions between product parts. Such a function model description is the ideal starting point for product innovation. Design engineers can apply (TRIZ) methods such as trimming and function ranking to this function model

  1. Introducing Trimming and Function Ranking to SolidWorks based on Function Analysis

    NARCIS (Netherlands)

    Chechurin, L.S.; Wits, Wessel Willems; Bakker, Hans M.; Vaneker, Thomas H.J.

    2015-01-01

    TRIZ based Function Analysis models existing products based on functional interactions between product parts. Such a function model description is the ideal starting point for product innovation. Design engineers can apply (TRIZ) methods such as trimming and function ranking to this function model

  2. Problem Solving in the Presence of Others: How Rank and Relationship Quality Impact Resource Acquisition in Chimpanzees (Pan troglodytes)

    Science.gov (United States)

    Cronin, Katherine A.; Pieper, Bridget A.; van Leeuwen, Edwin J. C.; Mundry, Roger; Haun, Daniel B. M.

    2014-01-01

    In the wild, chimpanzees (Pan troglodytes) are often faced with clumped food resources that they may know how to access but abstain from doing so due to social pressures. To better understand how social settings influence resource acquisition, we tested fifteen semi-wild chimpanzees from two social groups alone and in the presence of others. We investigated how resource acquisition was affected by relative social dominance, whether collaborative problem solving or (active or passive) sharing occurred amongst any of the dyads, and whether these outcomes were related to relationship quality as determined from six months of observational data. Results indicated that chimpanzees obtained fewer rewards when tested in the presence of others compared to when they were tested alone, and this loss tended to be greater when paired with a higher ranked individual. Individuals demonstrated behavioral inhibition; chimpanzees who showed proficient skill when alone often abstained from solving the task when in the presence of others. Finally, individuals with close social relationships spent more time together in the problem solving space, but collaboration and sharing were infrequent and sessions in which collaboration or sharing did occur contained more instances of aggression. Group living provides benefits and imposes costs, and these findings highlight that one cost of group living may be diminishing productive individual behaviors. PMID:24695486

  3. Problem solving in the presence of others: how rank and relationship quality impact resource acquisition in chimpanzees (Pan troglodytes.

    Directory of Open Access Journals (Sweden)

    Katherine A Cronin

    Full Text Available In the wild, chimpanzees (Pan troglodytes are often faced with clumped food resources that they may know how to access but abstain from doing so due to social pressures. To better understand how social settings influence resource acquisition, we tested fifteen semi-wild chimpanzees from two social groups alone and in the presence of others. We investigated how resource acquisition was affected by relative social dominance, whether collaborative problem solving or (active or passive sharing occurred amongst any of the dyads, and whether these outcomes were related to relationship quality as determined from six months of observational data. Results indicated that chimpanzees obtained fewer rewards when tested in the presence of others compared to when they were tested alone, and this loss tended to be greater when paired with a higher ranked individual. Individuals demonstrated behavioral inhibition; chimpanzees who showed proficient skill when alone often abstained from solving the task when in the presence of others. Finally, individuals with close social relationships spent more time together in the problem solving space, but collaboration and sharing were infrequent and sessions in which collaboration or sharing did occur contained more instances of aggression. Group living provides benefits and imposes costs, and these findings highlight that one cost of group living may be diminishing productive individual behaviors.

  4. New public management based on rankings: From plann ing to evaluation

    Directory of Open Access Journals (Sweden)

    Andrés Valdez Zepeda

    2017-11-01

    Full Text Available This article focuses on the emergence and development of a new trend of public affairs and global government management known as ranking-based management. This type of management process is the result of performance measurement usually conducted by an external agent or prestigious institution, which generally uses a methodology based on indicators and audits. It also evaluates the results, achievements and progress in governance, which it ranks on a list on which they are compared against other comparable governments. As a global trend, supported by management rankings this process is not seen as an option, but as a real requirement for public agencies and government, which not only helps them in the process of continuous improvement, but also creates important incentives such as prestige, social recognition, construction and better branding.

  5. BridgeRank: A novel fast centrality measure based on local structure of the network

    Science.gov (United States)

    Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

    2018-04-01

    Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

  6. An improved rank based disease prediction using web navigation patterns on bio-medical databases

    Directory of Open Access Journals (Sweden)

    P. Dhanalakshmi

    2017-12-01

    Full Text Available Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the document ranking models on biomedical database are sensitive to sparsity and outliers. In this paper, a novel user recommendation system was implemented to predict the top ranked biomedical documents using the disease type, gene entities and user navigation patterns. In this recommendation system, dynamic session identification, dynamic user identification and document ranking techniques were used to extract the highly relevant disease documents on the online PubMed repository. To verify the performance of the proposed model, the true positive rate and runtime of the model was compared with that of traditional static models such as Bayesian and Fuzzy rank. Experimental results show that the performance of the proposed ranking model is better than the traditional models.

  7. CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

    Science.gov (United States)

    Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

    2013-01-01

    Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

  8. Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

    Science.gov (United States)

    Mathur, Sunil; Sadana, Ajit

    2015-12-01

    We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

  9. Superstring motivated gauge models based on a rank six subgroup of E6

    International Nuclear Information System (INIS)

    Lazarides, G.; Panagiotakopoulos, C.; Shafi, Q.

    1987-01-01

    We discuss gauge models based on a superstring motivated rank six subgroup of E 6 . Lepton number is an accidental unbroken symmetry of the models which leads to an essential stable proton. One of the neutral gauge bosons couples to B-L and may have mass below a TeV. (orig.)

  10. Multi-Label Classification Based on Low Rank Representation for Image Annotation

    Directory of Open Access Journals (Sweden)

    Qiaoyu Tan

    2017-01-01

    Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

  11. Moral Entrepreneurship: Resource Based Ethics

    NARCIS (Netherlands)

    Pompe, V.M.M.

    2013-01-01

    This article studies the role of entrepreneurship in business ethics and promotes a resource-based ethics. The need for and usefulness of this form of ethics emerge from an analysis of contemporary business ethics that appears to be inefficacious and from a moral business practice formed out of the

  12. Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution

    International Nuclear Information System (INIS)

    Gong, Wenyin; Cai, Zhihua

    2013-01-01

    Parameter identification of PEM (proton exchange membrane) fuel cell model is a very active area of research. Generally, it can be treated as a numerical optimization problem with complex nonlinear and multi-variable features. DE (differential evolution), which has been successfully used in various fields, is a simple yet efficient evolutionary algorithm for global numerical optimization. In this paper, with the objective of accelerating the process of parameter identification of PEM fuel cell models and reducing the necessary computational efforts, we firstly present a generic and simple ranking-based mutation operator for the DE algorithm. Then, the ranking-based mutation operator is incorporated into five highly-competitive DE variants to solve the PEM fuel cell model parameter identification problems. The main contributions of this work are the proposed ranking-based DE variants and their application to the parameter identification problems of PEM fuel cell models. Experiments have been conducted by using both the simulated voltage–current data and the data obtained from the literature to validate the performance of our approach. The results indicate that the ranking-based DE methods provide better results with respect to the solution quality, the convergence rate, and the success rate compared with their corresponding original DE methods. In addition, the voltage–current characteristics obtained by our approach are in good agreement with the original voltage–current curves in all cases. - Highlights: • A simple and generic ranking-based mutation operator is presented in this paper. • Several DE (differential evolution) variants are used to solve the parameter identification of PEMFC (proton exchange membrane fuel cells) model. • Results show that our method accelerates the process of parameter identification. • The V–I characteristics are in very good agreement with experimental data

  13. Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback

    Science.gov (United States)

    Kountouris, Marios; Sälzer, Thomas; Gesbert, David

    2008-12-01

    We consider a multi-antenna broadcast channel with more single-antenna receivers than transmit antennas and partial channel state information at the transmitter (CSIT). We propose a novel type of CSIT representation for the purpose of user selection, coined as ranking-based feedback. Each user calculates and feeds back the rank, an integer between 1 and W + 1, of its instantaneous channel quality information (CQI) among a set of W past CQI measurements. Apart from reducing significantly the required feedback load, ranking-based feedback enables the transmitter to select users that are on the highest peak (quantile) with respect to their own channel distribution, independently of the distribution of other users. It can also be shown that this feedback metric can restore temporal fairness in heterogeneous networks, in which users' channels are not identically distributed and mobile terminals experience different average signal-to-noise ratio (SNR). The performance of a system that performs user selection using ranking-based CSIT in the context of random opportunistic beamforming is analyzed, and we provide design guidelines on the number of required past CSIT samples and the impact of finite W on average throughput. Simulation results show that feedback reduction of order of 40-50% can be achieved with negligible decrease in system throughput.

  14. A Simple Model to Rank Shellfish Farming Areas Based on the Risk of Disease Introduction and Spread.

    Science.gov (United States)

    Thrush, M A; Pearce, F M; Gubbins, M J; Oidtmann, B C; Peeler, E J

    2017-08-01

    The European Union Council Directive 2006/88/EC requires that risk-based surveillance (RBS) for listed aquatic animal diseases is applied to all aquaculture production businesses. The principle behind this is the efficient use of resources directed towards high-risk farm categories, animal types and geographic areas. To achieve this requirement, fish and shellfish farms must be ranked according to their risk of disease introduction and spread. We present a method to risk rank shellfish farming areas based on the risk of disease introduction and spread and demonstrate how the approach was applied in 45 shellfish farming areas in England and Wales. Ten parameters were used to inform the risk model, which were grouped into four risk themes based on related pathways for transmission of pathogens: (i) live animal movement, (ii) transmission via water, (iii) short distance mechanical spread (birds) and (iv) long distance mechanical spread (vessels). Weights (informed by expert knowledge) were applied both to individual parameters and to risk themes for introduction and spread to reflect their relative importance. A spreadsheet model was developed to determine quantitative scores for the risk of pathogen introduction and risk of pathogen spread for each shellfish farming area. These scores were used to independently rank areas for risk of introduction and for risk of spread. Thresholds were set to establish risk categories (low, medium and high) for introduction and spread based on risk scores. Risk categories for introduction and spread for each area were combined to provide overall risk categories to inform a risk-based surveillance programme directed at the area level. Applying the combined risk category designation framework for risk of introduction and spread suggested by European Commission guidance for risk-based surveillance, 4, 10 and 31 areas were classified as high, medium and low risk, respectively. © 2016 Crown copyright.

  15. Ranking of energy resources within the analysis of total costs for the IRP (Integrated Resources Planning for Energy Resources); Ranqueamento de recursos energeticos dentro da analise de custos completos para o PIR (Planejamento Integrado de Recursos Energeticos)

    Energy Technology Data Exchange (ETDEWEB)

    Reinig, Alexandre Orrico; Cicone Junior, Decio; Galvao, Luiz Claudio Ribeiro [Universidade de Sao Paulo (USP), SP (Brazil). Dept. de Energia e Automacao Eletricas. Grupo de Energia; Udaeta, Miguel Edgar Morales [Universidade de Sao Paulo (USP), SP (Brazil). Inst. de Eletrotecnica e Energia

    2008-07-01

    The objective of this work is to demonstrate the application of the Analytic Hierarchy Process (PAH) with the support of computational tools in the Complete Costs Evaluation (ACC) to classify energy resources, emphasizing as this important method of decision making can be used with the ACC inside of the integrated resources planning for energy resources (PIR). The use of the methodology in question inside of the PIR has as permanent goal to interrelate the complete technical valuation of the resources and its qualitative valuation carried through by the involved and interested (En-In) of the PIR, as well as the evaluation of the resources inside of multidimensional criteria of the ACC. For this the way is presented the way as the evaluation of the social dimension of the ACC in the PIR in the Aracatuba's Administrative Region (RAA) was made and ranking generated with the application of the PAH inside of the ACC. The main result is the validation of the AHP with the use of the Decision Lens for the ACC in the PIR, and from that conclude that the ranking of many energy resources using Decision Lens facilitates the process of PIR in the posterior Wallet of Resources and preferential plan determination. (author)

  16. Network-based ranking methods for prediction of novel disease associated microRNAs.

    Science.gov (United States)

    Le, Duc-Hau

    2015-10-01

    Many studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a "disease module" principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the "disease module" principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction. We constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm. Analyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In

  17. Environmental and health hazard ranking and assessment of plastic polymers based on chemical composition

    Energy Technology Data Exchange (ETDEWEB)

    Lithner, Delilah, E-mail: delilah.lithner@gmail.com; Larsson, Ake; Dave, Goeran

    2011-08-15

    Plastics constitute a large material group with a global annual production that has doubled in 15 years (245 million tonnes in 2008). Plastics are present everywhere in society and the environment, especially the marine environment, where large amounts of plastic waste accumulate. The knowledge of human and environmental hazards and risks from chemicals associated with the diversity of plastic products is very limited. Most chemicals used for producing plastic polymers are derived from non-renewable crude oil, and several are hazardous. These may be released during the production, use and disposal of the plastic product. In this study the environmental and health hazards of chemicals used in 55 thermoplastic and thermosetting polymers were identified and compiled. A hazard ranking model was developed for the hazard classes and categories in the EU classification and labelling (CLP) regulation which is based on the UN Globally Harmonized System. The polymers were ranked based on monomer hazard classifications, and initial assessments were made. The polymers that ranked as most hazardous are made of monomers classified as mutagenic and/or carcinogenic (category 1A or 1B). These belong to the polymer families of polyurethanes, polyacrylonitriles, polyvinyl chloride, epoxy resins, and styrenic copolymers. All have a large global annual production (1-37 million tonnes). A considerable number of polymers (31 out of 55) are made of monomers that belong to the two worst of the ranking model's five hazard levels, i.e. levels IV-V. The polymers that are made of level IV monomers and have a large global annual production (1-5 million tonnes) are phenol formaldehyde resins, unsaturated polyesters, polycarbonate, polymethyl methacrylate, and urea-formaldehyde resins. This study has identified hazardous substances used in polymer production for which the risks should be evaluated for decisions on the need for risk reduction measures, substitution, or even phase out

  18. A Multiobjective Programming Method for Ranking All Units Based on Compensatory DEA Model

    Directory of Open Access Journals (Sweden)

    Haifang Cheng

    2014-01-01

    Full Text Available In order to rank all decision making units (DMUs on the same basis, this paper proposes a multiobjective programming (MOP model based on a compensatory data envelopment analysis (DEA model to derive a common set of weights that can be used for the full ranking of all DMUs. We first revisit a compensatory DEA model for ranking all units, point out the existing problem for solving the model, and present an improved algorithm for which an approximate global optimal solution of the model can be obtained by solving a sequence of linear programming. Then, we applied the key idea of the compensatory DEA model to develop the MOP model in which the objectives are to simultaneously maximize all common weights under constraints that the sum of efficiency values of all DMUs is equal to unity and the sum of all common weights is also equal to unity. In order to solve the MOP model, we transform it into a single objective programming (SOP model using a fuzzy programming method and solve the SOP model using the proposed approximation algorithm. To illustrate the ranking method using the proposed method, two numerical examples are solved.

  19. A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

    Science.gov (United States)

    Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

    2012-04-01

    We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

  20. Virtual drug screen schema based on multiview similarity integration and ranking aggregation.

    Science.gov (United States)

    Kang, Hong; Sheng, Zhen; Zhu, Ruixin; Huang, Qi; Liu, Qi; Cao, Zhiwei

    2012-03-26

    The current drug virtual screen (VS) methods mainly include two categories. i.e., ligand/target structure-based virtual screen and that, utilizing protein-ligand interaction fingerprint information based on the large number of complex structures. Since the former one focuses on the one-side information while the later one focuses on the whole complex structure, they are thus complementary and can be boosted by each other. However, a common problem faced here is how to present a comprehensive understanding and evaluation of the various virtual screen results derived from various VS methods. Furthermore, there is still an urgent need for developing an efficient approach to fully integrate various VS methods from a comprehensive multiview perspective. In this study, our virtual screen schema based on multiview similarity integration and ranking aggregation was tested comprehensively with statistical evaluations, providing several novel and useful clues on how to perform drug VS from multiple heterogeneous data sources. (1) 18 complex structures of HIV-1 protease with ligands from the PDB were curated as a test data set and the VS was performed with five different drug representations. Ritonavir ( 1HXW ) was selected as the query in VS and the weighted ranks of the query results were aggregated from multiple views through four similarity integration approaches. (2) Further, one of the ranking aggregation methods was used to integrate the similarity ranks calculated by gene ontology (GO) fingerprint and structural fingerprint on the data set from connectivity map, and two typical HDAC and HSP90 inhibitors were chosen as the queries. The results show that rank aggregation can enhance the result of similarity searching in VS when two or more descriptions are involved and provide a more reasonable similarity rank result. Our study shows that integrated VS based on multiple data fusion can achieve a remarkable better performance compared to that from individual ones and

  1. A gender-based comparison of academic rank and scholarly productivity in academic neurological surgery.

    Science.gov (United States)

    Tomei, Krystal L; Nahass, Meghan M; Husain, Qasim; Agarwal, Nitin; Patel, Smruti K; Svider, Peter F; Eloy, Jean Anderson; Liu, James K

    2014-07-01

    The number of women pursuing training opportunities in neurological surgery has increased, although they are still underrepresented at senior positions relative to junior academic ranks. Research productivity is an important component of the academic advancement process. We sought to use the h-index, a bibliometric previously analyzed among neurological surgeons, to evaluate whether there are gender differences in academic rank and research productivity among academic neurological surgeons. The h-index was calculated for 1052 academic neurological surgeons from 84 institutions, and organized by gender and academic rank. Overall men had statistically higher research productivity (mean 13.3) than their female colleagues (mean 9.5), as measured by the h-index, in the overall sample (p0.05) in h-index at the assistant professor (mean 7.2 male, 6.3 female), associate professor (11.2 male, 10.8 female), and professor (20.0 male, 18.0 female) levels based on gender. There was insufficient data to determine significance at the chairperson rank, as there was only one female chairperson. Although overall gender differences in scholarly productivity were detected, these differences did not reach statistical significance upon controlling for academic rank. Women were grossly underrepresented at the level of chairpersons in this sample of 1052 academic neurological surgeons, likely a result of the low proportion of females in this specialty. Future studies may be needed to investigate gender-specific research trends for neurosurgical residents, a cohort that in recent years has seen increased representation by women. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

    Science.gov (United States)

    Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

    2009-11-01

    A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

  3. Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting.

    Science.gov (United States)

    Hoshikawa, K; Ono, S

    2017-02-01

    Multicriteria decision analysis (MCDA) has been generally considered a promising decision-making methodology for the assessment of drug benefit-risk profiles. There have been many discussions in both public and private sectors on its feasibility and applicability, but it has not been employed in official decision-makings. For the purpose of examining to what extent MCDA would reflect the first-hand, intuitive preference of evaluators in practical pharmaceutical assessments, we conducted a questionnaire survey involving the participation of employees of pharmaceutical companies. Showing profiles of the efficacy and safety of four hypothetical drugs, each respondent was asked to rank them following the standard MCDA process and then to rank them intuitively (i.e. without applying any analytical framework). These two approaches resulted in substantially different ranking patterns from the same individuals, and the concordance rate was surprisingly low (17%). Although many respondents intuitively showed a preference for mild, balanced risk-benefit profiles over profiles with a conspicuous advantage in either risk or benefit, the ranking orders based on MCDA scores did not reflect the intuitive preference. Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment. © 2016 John Wiley & Sons Ltd.

  4. A rank based social norms model of how people judge their levels of drunkenness whilst intoxicated

    Directory of Open Access Journals (Sweden)

    Simon C. Moore

    2016-09-01

    Full Text Available Abstract Background A rank based social norms model predicts that drinkers’ judgements about their drinking will be based on the rank of their breath alcohol level amongst that of others in the immediate environment, rather than their actual breath alcohol level, with lower relative rank associated with greater feelings of safety. This study tested this hypothesis and examined how people judge their levels of drunkenness and the health consequences of their drinking whilst they are intoxicated in social drinking environments. Methods Breath alcohol testing of 1,862 people (mean age = 26.96 years; 61.86 % male in drinking environments. A subset (N = 400 also answered four questions asking about their perceptions of their drunkenness and the health consequences of their drinking (plus background measures. Results Perceptions of drunkenness and the health consequences of drinking were regressed on: (a breath alcohol level, (b the rank of the breath alcohol level amongst that of others in the same environment, and (c covariates. Only rank of breath alcohol level predicted perceptions: How drunk they felt (b 3.78, 95 % CI 1.69 5.87, how extreme they regarded their drinking that night (b 3.7, 95 % CI 1.3 6.20, how at risk their long-term health was due to their current level of drinking (b 4.1, 95 % CI 0.2 8.0 and how likely they felt they would experience liver cirrhosis (b 4.8. 95 % CI 0.7 8.8. People were more influenced by more sober others than by more drunk others. Conclusion Whilst intoxicated and in drinking environments, people base judgements regarding their drinking on how their level of intoxication ranks relative to that of others of the same gender around them, not on their actual levels of intoxication. Thus, when in the company of others who are intoxicated, drinkers were found to be more likely to underestimate their own level of drinking, drunkenness and associated risks. The implications of these results, for example

  5. Fabric defect detection based on visual saliency using deep feature and low-rank recovery

    Science.gov (United States)

    Liu, Zhoufeng; Wang, Baorui; Li, Chunlei; Li, Bicao; Dong, Yan

    2018-04-01

    Fabric defect detection plays an important role in improving the quality of fabric product. In this paper, a novel fabric defect detection method based on visual saliency using deep feature and low-rank recovery was proposed. First, unsupervised training is carried out by the initial network parameters based on MNIST large datasets. The supervised fine-tuning of fabric image library based on Convolutional Neural Networks (CNNs) is implemented, and then more accurate deep neural network model is generated. Second, the fabric images are uniformly divided into the image block with the same size, then we extract their multi-layer deep features using the trained deep network. Thereafter, all the extracted features are concentrated into a feature matrix. Third, low-rank matrix recovery is adopted to divide the feature matrix into the low-rank matrix which indicates the background and the sparse matrix which indicates the salient defect. In the end, the iterative optimal threshold segmentation algorithm is utilized to segment the saliency maps generated by the sparse matrix to locate the fabric defect area. Experimental results demonstrate that the feature extracted by CNN is more suitable for characterizing the fabric texture than the traditional LBP, HOG and other hand-crafted features extraction method, and the proposed method can accurately detect the defect regions of various fabric defects, even for the image with complex texture.

  6. Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication

    Directory of Open Access Journals (Sweden)

    Tong Wang

    2017-01-01

    Full Text Available In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G mobile communication networks, among which device-to-device (D2D communication is one of the key technologies. Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. In opportunistic networks, in case of encountering nodes which never meet before a flood message blindly to cause tremendous network overhead, a novel opportunistic network routing protocol based on social rank and intermeeting time (SRIT is proposed in this paper. An improved utility approach applied in utility replication based on encounter durations and intermeeting time is put forward to enhance the routing efficiency. Meanwhile, in order to select better candidate nodes in the network, a social graph among people is established when they socially relate to each other in social rank replication. The results under the scenario show an advantage of the proposed opportunistic network routing based on social rank and intermeeting time (SRIT over the compared algorithms in terms of delivery ratio, average delivery latency, and overhead ratio.

  7. An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking

    Directory of Open Access Journals (Sweden)

    Sujay Saha

    2016-01-01

    Full Text Available Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382, Breast Cancer dataset (GSE349-350, Prostate Cancer dataset, and DLBCL-FL (Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.

  8. PageRank, HITS and a unified framework for link analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Chris; He, Xiaofeng; Husbands, Parry; Zha, Hongyuan; Simon, Horst

    2001-10-01

    Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight normalization and web surfing based on random walk models. We systematically generalize/combine these concepts into a unified framework. The ranking framework contains a large algorithm space; HITS and PageRank are two extreme ends in this space. We study several normalized ranking algorithms which are intermediate between HITS and PageRank, and obtain closed-form solutions. We show that, to first order approximation, all ranking algorithms in this framework, including PageRank and HITS, lead to same ranking which is highly correlated with ranking by indegree. These results support the notion that in web resource ranking indegree and outdegree are of fundamental importance. Rankings of webgraphs of different sizes and queries are presented to illustrate our analysis.

  9. Ranking Operations Management conferences

    NARCIS (Netherlands)

    Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

    2007-01-01

    Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

  10. Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Hongyang Lu

    2016-06-01

    Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

  11. Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation

    Directory of Open Access Journals (Sweden)

    Pandiarajan K.

    2014-09-01

    Full Text Available This paper presents an effective method of network overload management in power systems. The three competing objectives 1 generation cost 2 transmission line overload and 3 real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO and Differential evolution (DE. Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem

  12. Development of a health effects based priority ranking system for air emissions reductions from oil refineries in Canada

    International Nuclear Information System (INIS)

    McColl, S.; Gower, S.; Hicks, J.; Shortreed, J.; Craig, L.

    2004-01-01

    This paper presents the concept and methodologies behind the development of a health effects priority ranking tool for the reduction of air emissions from oil refineries. The Health Effects Indicators Decision Index- Versions 2 (Heidi II) was designed to assist policy makers in prioritizing air emissions reductions on the basis of estimated risk to human health. Inputs include facility level rankings of potential health impacts associated with carcinogenic air toxics, non-carcinogenic air toxics and criteria air contaminants for each of the 20 refineries in Canada. Rankings of estimated health impacts are presented on predicted incidence of health effects. Heidi II considers site-specific annual pollutant emission data, ambient air concentrations associated with releases and concentration response functions for various types of health effects. Additional data includes location specific background air concentrations, site-specific population densities, and the baseline incidence of different health effects endpoints, such as cancer, non-cancer illnesses and cardiorespiratory illnesses and death. Air pollutants include the 29 air toxics reported annually in Environment Canada's National Pollutant Release Inventory. Three health impact ranking outputs are provided for each facility: ranking of pollutants based on predicted number of annual cases of health effects; ranking of pollutants based on simplified Disability Adjusted Life Years (DALYs); and ranking of pollutants based on more complex DALYs that consider types of cancer, systemic disease or types of cardiopulmonary health effects. Rankings rely on rough statistical estimates of predicted incidence rates for health endpoints. The models used to calculate rankings can provide useful guidance by comparing estimated health impacts. Heidi II has demonstrated that it is possible to develop a consistent and objective approach for ranking priority reductions of air emissions. Heidi II requires numerous types and

  13. A LDA-based approach to promoting ranking diversity for genomics information retrieval.

    Science.gov (United States)

    Chen, Yan; Yin, Xiaoshi; Li, Zhoujun; Hu, Xiaohua; Huang, Jimmy Xiangji

    2012-06-11

    In the biomedical domain, there are immense data and tremendous increase of genomics and biomedical relevant publications. The wealth of information has led to an increasing amount of interest in and need for applying information retrieval techniques to access the scientific literature in genomics and related biomedical disciplines. In many cases, the desired information of a query asked by biologists is a list of a certain type of entities covering different aspects that are related to the question, such as cells, genes, diseases, proteins, mutations, etc. Hence, it is important of a biomedical IR system to be able to provide relevant and diverse answers to fulfill biologists' information needs. However traditional IR model only concerns with the relevance between retrieved documents and user query, but does not take redundancy between retrieved documents into account. This will lead to high redundancy and low diversity in the retrieval ranked lists. In this paper, we propose an approach which employs a topic generative model called Latent Dirichlet Allocation (LDA) to promoting ranking diversity for biomedical information retrieval. Different from other approaches or models which consider aspects on word level, our approach assumes that aspects should be identified by the topics of retrieved documents. We present LDA model to discover topic distribution of retrieval passages and word distribution of each topic dimension, and then re-rank retrieval results with topic distribution similarity between passages based on N-size slide window. We perform our approach on TREC 2007 Genomics collection and two distinctive IR baseline runs, which can achieve 8% improvement over the highest Aspect MAP reported in TREC 2007 Genomics track. The proposed method is the first study of adopting topic model to genomics information retrieval, and demonstrates its effectiveness in promoting ranking diversity as well as in improving relevance of ranked lists of genomics search

  14. Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

    Directory of Open Access Journals (Sweden)

    Lieven P C Verbeke

    Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

  15. Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  16. Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition.

    Science.gov (United States)

    Tao, Dapeng; Jin, Lianwen; Yuan, Yuan; Xue, Yang

    2016-06-01

    With the rapid development of mobile devices and pervasive computing technologies, acceleration-based human activity recognition, a difficult yet essential problem in mobile apps, has received intensive attention recently. Different acceleration signals for representing different activities or even a same activity have different attributes, which causes troubles in normalizing the signals. We thus cannot directly compare these signals with each other, because they are embedded in a nonmetric space. Therefore, we present a nonmetric scheme that retains discriminative and robust frequency domain information by developing a novel ensemble manifold rank preserving (EMRP) algorithm. EMRP simultaneously considers three aspects: 1) it encodes the local geometry using the ranking order information of intraclass samples distributed on local patches; 2) it keeps the discriminative information by maximizing the margin between samples of different classes; and 3) it finds the optimal linear combination of the alignment matrices to approximate the intrinsic manifold lied in the data. Experiments are conducted on the South China University of Technology naturalistic 3-D acceleration-based activity dataset and the naturalistic mobile-devices based human activity dataset to demonstrate the robustness and effectiveness of the new nonmetric scheme for acceleration-based human activity recognition.

  17. Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

    Directory of Open Access Journals (Sweden)

    Rakesh Garg

    2015-06-01

    Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

  18. Structure-Based Low-Rank Model With Graph Nuclear Norm Regularization for Noise Removal.

    Science.gov (United States)

    Ge, Qi; Jing, Xiao-Yuan; Wu, Fei; Wei, Zhi-Hui; Xiao, Liang; Shao, Wen-Ze; Yue, Dong; Li, Hai-Bo

    2017-07-01

    Nonlocal image representation methods, including group-based sparse coding and block-matching 3-D filtering, have shown their great performance in application to low-level tasks. The nonlocal prior is extracted from each group consisting of patches with similar intensities. Grouping patches based on intensity similarity, however, gives rise to disturbance and inaccuracy in estimation of the true images. To address this problem, we propose a structure-based low-rank model with graph nuclear norm regularization. We exploit the local manifold structure inside a patch and group the patches by the distance metric of manifold structure. With the manifold structure information, a graph nuclear norm regularization is established and incorporated into a low-rank approximation model. We then prove that the graph-based regularization is equivalent to a weighted nuclear norm and the proposed model can be solved by a weighted singular-value thresholding algorithm. Extensive experiments on additive white Gaussian noise removal and mixed noise removal demonstrate that the proposed method achieves a better performance than several state-of-the-art algorithms.

  19. Pareto-Ranking Based Quantum-Behaved Particle Swarm Optimization for Multiobjective Optimization

    Directory of Open Access Journals (Sweden)

    Na Tian

    2015-01-01

    Full Text Available A study on pareto-ranking based quantum-behaved particle swarm optimization (QPSO for multiobjective optimization problems is presented in this paper. During the iteration, an external repository is maintained to remember the nondominated solutions, from which the global best position is chosen. The comparison between different elitist selection strategies (preference order, sigma value, and random selection is performed on four benchmark functions and two metrics. The results demonstrate that QPSO with preference order has comparative performance with sigma value according to different number of objectives. Finally, QPSO with sigma value is applied to solve multiobjective flexible job-shop scheduling problems.

  20. A rapid place name locating algorithm based on ontology qualitative retrieval, ranking and recommendation

    Science.gov (United States)

    Fan, Hong; Zhu, Anfeng; Zhang, Weixia

    2015-12-01

    In order to meet the rapid positioning of 12315 complaints, aiming at the natural language expression of telephone complaints, a semantic retrieval framework is proposed which is based on natural language parsing and geographical names ontology reasoning. Among them, a search result ranking and recommended algorithms is proposed which is regarding both geo-name conceptual similarity and spatial geometry relation similarity. The experiments show that this method can assist the operator to quickly find location of 12,315 complaints, increased industry and commerce customer satisfaction.

  1. The Urban Transition Performance of Resource-Based Cities in Northeast China

    Directory of Open Access Journals (Sweden)

    Juntao Tan

    2016-10-01

    Full Text Available Resource-based cities face unique challenges when undergoing urban transitions because their non-renewable resources will eventually be exhausted. In this article, we introduce a new method of evaluating the urban transition performance of resource-based cities from economic, social and eco-environmental perspectives. A total of 19 resource-based cities in Northeast China are studied from 2003 to 2012. The results show that resource-based cities in Jilin and Liaoning provinces performed better than those in Heilongjiang province. Liaoyuan, Songyuan and Baishan were ranked as the top three resource-based cities; and Jixi, Yichun and Heihe were ranked last. Multi-resource and petroleum resource-based cities performed better than coal and forestry resource-based cities. We also analyzed the factors influencing urban transition performance using the method of the geographic detector. We found that capital input, road density and location advantage had the greatest effects on urban transition performance, followed by urban scale, remaining resources and the level of sustainable development; supporting policies and labor input had the smallest effects. Based on these insights, we have formulated several recommendations to facilitate urban transitions in China’s resource-based cities.

  2. Environmental restoration risk-based prioritization work package planning and risk ranking methodology. Revision 2

    International Nuclear Information System (INIS)

    Dail, J.L.; Nanstad, L.D.; White, R.K.

    1995-06-01

    This document presents the risk-based prioritization methodology developed to evaluate and rank Environmental Restoration (ER) work packages at the five US Department of Energy, Oak Ridge Field Office (DOE-ORO) sites [i.e., Oak Ridge K-25 Site (K-25), Portsmouth Gaseous Diffusion Plant (PORTS), Paducah Gaseous Diffusion Plant (PGDP), Oak Ridge National Laboratory (ORNL), and the Oak Ridge Y-12 Plant (Y-12)], the ER Off-site Program, and Central ER. This prioritization methodology was developed to support the increased rigor and formality of work planning in the overall conduct of operations within the DOE-ORO ER Program. Prioritization is conducted as an integral component of the fiscal ER funding cycle to establish program budget priorities. The purpose of the ER risk-based prioritization methodology is to provide ER management with the tools and processes needed to evaluate, compare, prioritize, and justify fiscal budget decisions for a diverse set of remedial action, decontamination and decommissioning, and waste management activities. The methodology provides the ER Program with a framework for (1) organizing information about identified DOE-ORO environmental problems, (2) generating qualitative assessments of the long- and short-term risks posed by DOE-ORO environmental problems, and (3) evaluating the benefits associated with candidate work packages designed to reduce those risks. Prioritization is conducted to rank ER work packages on the basis of the overall value (e.g., risk reduction, stakeholder confidence) each package provides to the ER Program. Application of the methodology yields individual work package ''scores'' and rankings that are used to develop fiscal budget requests. This document presents the technical basis for the decision support tools and process

  3. SQERTSS: Dynamic rank based throttling of transition probabilities in kinetic Monte Carlo simulations

    International Nuclear Information System (INIS)

    Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; Virginia Polytechnic Institute and State University; Savara, Aditya

    2017-01-01

    Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of “KMC stiffness” (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps / cpu-time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order to achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events -- allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm designed for use in achieving and simulating steady-state conditions in KMC simulations. Lastly, as shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.

  4. An Automatic Web Service Composition Framework Using QoS-Based Web Service Ranking Algorithm.

    Science.gov (United States)

    Mallayya, Deivamani; Ramachandran, Baskaran; Viswanathan, Suganya

    2015-01-01

    Web service has become the technology of choice for service oriented computing to meet the interoperability demands in web applications. In the Internet era, the exponential addition of web services nominates the "quality of service" as essential parameter in discriminating the web services. In this paper, a user preference based web service ranking (UPWSR) algorithm is proposed to rank web services based on user preferences and QoS aspect of the web service. When the user's request cannot be fulfilled by a single atomic service, several existing services should be composed and delivered as a composition. The proposed framework allows the user to specify the local and global constraints for composite web services which improves flexibility. UPWSR algorithm identifies best fit services for each task in the user request and, by choosing the number of candidate services for each task, reduces the time to generate the composition plans. To tackle the problem of web service composition, QoS aware automatic web service composition (QAWSC) algorithm proposed in this paper is based on the QoS aspects of the web services and user preferences. The proposed framework allows user to provide feedback about the composite service which improves the reputation of the services.

  5. A GIS based screening tool for locating and ranking of suitable stormwater harvesting sites in urban areas.

    Science.gov (United States)

    Inamdar, P M; Cook, S; Sharma, A K; Corby, N; O'Connor, J; Perera, B J C

    2013-10-15

    There is the need to re-configure current urban water systems to achieve the objective of sustainable water sensitive cities. Stormwater represents a valuable alternative urban water source to reduce pressure on fresh water resources, and to mitigate the environmental impact of urban stormwater runoff. The selection of suitable urban stormwater harvesting sites is generally based on the judgement of water planners, who are faced with the challenge of considering multiple technical and socio-economic factors that influence the site suitability. To address this challenge, the present study developed a robust GIS based screening methodology for identifying potentially suitable stormwater harvesting sites in urban areas as a first pass for then more detailed investigation. The study initially evaluated suitability based on the match between harvestable runoff and demand through a concept of accumulated catchments. Drainage outlets of these accumulated catchments were considered as potential stormwater harvesting sites. These sites were screened and ranked under screening parameters namely demand, ratio of runoff to demand and weighted demand distance. The methodology described in this paper was successfully applied to a case study in Melbourne, Australia in collaboration with the local water utility. The methodology was found to be effective in supporting the selection of priority sites for stormwater harvesting schemes, as it provided the basis to identify, short-list and rank sites for further detailed investigation. The rapid identification of suitable sites for stormwater harvesting can assist planners in prioritising schemes in areas that will have the most impact on reducing potable water demand. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Grid-based lattice summation of electrostatic potentials by assembled rank-structured tensor approximation

    Science.gov (United States)

    Khoromskaia, Venera; Khoromskij, Boris N.

    2014-12-01

    Our recent method for low-rank tensor representation of sums of the arbitrarily positioned electrostatic potentials discretized on a 3D Cartesian grid reduces the 3D tensor summation to operations involving only 1D vectors however retaining the linear complexity scaling in the number of potentials. Here, we introduce and study a novel tensor approach for fast and accurate assembled summation of a large number of lattice-allocated potentials represented on 3D N × N × N grid with the computational requirements only weakly dependent on the number of summed potentials. It is based on the assembled low-rank canonical tensor representations of the collected potentials using pointwise sums of shifted canonical vectors representing the single generating function, say the Newton kernel. For a sum of electrostatic potentials over L × L × L lattice embedded in a box the required storage scales linearly in the 1D grid-size, O(N) , while the numerical cost is estimated by O(NL) . For periodic boundary conditions, the storage demand remains proportional to the 1D grid-size of a unit cell, n = N / L, while the numerical cost reduces to O(N) , that outperforms the FFT-based Ewald-type summation algorithms of complexity O(N3 log N) . The complexity in the grid parameter N can be reduced even to the logarithmic scale O(log N) by using data-sparse representation of canonical N-vectors via the quantics tensor approximation. For justification, we prove an upper bound on the quantics ranks for the canonical vectors in the overall lattice sum. The presented approach is beneficial in applications which require further functional calculus with the lattice potential, say, scalar product with a function, integration or differentiation, which can be performed easily in tensor arithmetics on large 3D grids with 1D cost. Numerical tests illustrate the performance of the tensor summation method and confirm the estimated bounds on the tensor ranks.

  7. Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

    Directory of Open Access Journals (Sweden)

    Fengjian Shi

    2017-10-01

    Full Text Available In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster–Shafer evidence theory (D–S theory has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D–S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

  8. Fuzzy Group Decision Making Approach for Ranking Work Stations Based on Physical Pressure

    Directory of Open Access Journals (Sweden)

    Hamed Salmanzadeh

    2014-06-01

    Full Text Available This paper proposes a Fuzzy Group Decision Making approach for ranking work stations based on physical pressure. Fuzzy group decision making approach allows experts to evaluate different ergonomic factors using linguistic terms such as very high, high, medium, low, very low, rather than precise numerical values. In this way, there is no need to measure parameters and evaluation can be easily made in a group. According to ergonomics much work contents and situations, accompanied with multiple parameters and uncertainties, fuzzy group decision making is the best way to evaluate such a chameleon of concept. A case study was down to utilize the approach and illustrate its application in ergonomic assessment and ranking the work stations based on work pressure and found that this approach provides flexibility, practicality, efficiency in making decision around ergonomics areas. The normalized defuzzification numbers which are resulted from this method are compared with result of quantitative assessment of Automotive Assembly Work Sheet auto, it’s demonstrated that the proposed method result is 10% less than Automotive Assembly Work Sheet, approximately.

  9. Incorporating linguistic, probabilistic, and possibilistic information in a risk-based approach for ranking contaminated sites.

    Science.gov (United States)

    Zhang, Kejiang; Achari, Gopal; Pei, Yuansheng

    2010-10-01

    Different types of uncertain information-linguistic, probabilistic, and possibilistic-exist in site characterization. Their representation and propagation significantly influence the management of contaminated sites. In the absence of a framework with which to properly represent and integrate these quantitative and qualitative inputs together, decision makers cannot fully take advantage of the available and necessary information to identify all the plausible alternatives. A systematic methodology was developed in the present work to incorporate linguistic, probabilistic, and possibilistic information into the Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), a subgroup of Multi-Criteria Decision Analysis (MCDA) methods for ranking contaminated sites. The identification of criteria based on the paradigm of comparative risk assessment provides a rationale for risk-based prioritization. Uncertain linguistic, probabilistic, and possibilistic information identified in characterizing contaminated sites can be properly represented as numerical values, intervals, probability distributions, and fuzzy sets or possibility distributions, and linguistic variables according to their nature. These different kinds of representation are first transformed into a 2-tuple linguistic representation domain. The propagation of hybrid uncertainties is then carried out in the same domain. This methodology can use the original site information directly as much as possible. The case study shows that this systematic methodology provides more reasonable results. © 2010 SETAC.

  10. Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

    Science.gov (United States)

    Shi, Fengjian; Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

    2017-10-16

    In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster-Shafer evidence theory (D-S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D-S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

  11. Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

    Science.gov (United States)

    Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra

    2017-06-01

    In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

  12. Rank Dynamics

    Science.gov (United States)

    Gershenson, Carlos

    Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

  13. A comparison of average-based, percentile rank, and other citation impact indicators

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz-Castillo, J.; Albarran, P.

    2016-07-01

    The main aim of this paper is to defend the view that, in spite of the broad agreement in favor of the MNCS and the percentile rank indicators, there are two other citation indicators with desirable properties that the above indicators do not posses: (i) a member of the family of high-impact indicators introduced in Albarránet al. (2011), and (ii) a new indicator, based in the work of Herrero & Villar (2013), which measures the relative performance of the different research units in terms of a series of tournaments in which each research unit is confronted with all others repeatedly. We compare indicators from the point of view of their discriminatory power, measured by the range and the coefficient of variation. Using a large dataset indexed by Thomson Reuters, we consider 40 countries that have published at least 10,000 articles in all sciences in 1998-2003. There are two main findings. First, the new indicator exhibits a greater discriminatory power than percentile rank indicators. Second, the high-impact indicator exhibits the greatest discriminatory power. (Author)

  14. Feature selection model based on clustering and ranking in pipeline for microarray data

    Directory of Open Access Journals (Sweden)

    Barnali Sahu

    2017-01-01

    Full Text Available Most of the available feature selection techniques in the literature are classifier bound. It means a group of features tied to the performance of a specific classifier as applied in wrapper and hybrid approach. Our objective in this study is to select a set of generic features not tied to any classifier based on the proposed framework. This framework uses attribute clustering and feature ranking techniques in pipeline in order to remove redundant features. On each uncovered cluster, signal-to-noise ratio, t-statistics and significance analysis of microarray are independently applied to select the top ranked features. Both filter and evolutionary wrapper approaches have been considered for feature selection and the data set with selected features are given to ensemble of predefined statistically different classifiers. The class labels of the test data are determined using majority voting technique. Moreover, with the aforesaid objectives, this paper focuses on obtaining a stable result out of various classification models. Further, a comparative analysis has been performed to study the classification accuracy and computational time of the current approach and evolutionary wrapper techniques. It gives a better insight into the features and further enhancing the classification accuracy with less computational time.

  15. Entropy-based gene ranking without selection bias for the predictive classification of microarray data

    Directory of Open Access Journals (Sweden)

    Serafini Maria

    2003-11-01

    Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

  16. Feature selection for splice site prediction: A new method using EDA-based feature ranking

    Directory of Open Access Journals (Sweden)

    Rouzé Pierre

    2004-05-01

    Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

  17. Rank-defective millimeter-wave channel estimation based on subspace-compressive sensing

    Directory of Open Access Journals (Sweden)

    Majid Shakhsi Dastgahian

    2016-11-01

    Full Text Available Millimeter-wave communication (mmWC is considered as one of the pioneer candidates for 5G indoor and outdoor systems in E-band. To subdue the channel propagation characteristics in this band, high dimensional antenna arrays need to be deployed at both the base station (BS and mobile sets (MS. Unlike the conventional MIMO systems, Millimeter-wave (mmW systems lay away to employ the power predatory equipment such as ADC or RF chain in each branch of MIMO system because of hardware constraints. Such systems leverage to the hybrid precoding (combining architecture for downlink deployment. Because there is a large array at the transceiver, it is impossible to estimate the channel by conventional methods. This paper develops a new algorithm to estimate the mmW channel by exploiting the sparse nature of the channel. The main contribution is the representation of a sparse channel model and the exploitation of a modified approach based on Multiple Measurement Vector (MMV greedy sparse framework and subspace method of Multiple Signal Classification (MUSIC which work together to recover the indices of non-zero elements of an unknown channel matrix when the rank of the channel matrix is defected. In practical rank-defective channels, MUSIC fails, and we need to propose new extended MUSIC approaches based on subspace enhancement to compensate the limitation of MUSIC. Simulation results indicate that our proposed extended MUSIC algorithms will have proper performances and moderate computational speeds, and that they are even able to work in channels with an unknown sparsity level.

  18. Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition

    Directory of Open Access Journals (Sweden)

    yuan Shuai

    2017-01-01

    Full Text Available In this paper, a new subspace speech enhancement method using low-rank and sparse decomposition is presented. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal. Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise. Extensive experiments have been carried out in white Gaussian noise condition, and experimental results show the proposed method performs better than conventional speech enhancement methods, in terms of yielding less residual noise and lower speech distortion.

  19. A Direct Elliptic Solver Based on Hierarchically Low-Rank Schur Complements

    KAUST Repository

    Chávez, Gustavo

    2017-03-17

    A parallel fast direct solver for rank-compressible block tridiagonal linear systems is presented. Algorithmic synergies between Cyclic Reduction and Hierarchical matrix arithmetic operations result in a solver with O(Nlog2N) arithmetic complexity and O(NlogN) memory footprint. We provide a baseline for performance and applicability by comparing with well-known implementations of the $$\\\\mathcal{H}$$ -LU factorization and algebraic multigrid within a shared-memory parallel environment that leverages the concurrency features of the method. Numerical experiments reveal that this method is comparable with other fast direct solvers based on Hierarchical Matrices such as $$\\\\mathcal{H}$$ -LU and that it can tackle problems where algebraic multigrid fails to converge.

  20. Wilcoxon signed-rank-based technique for the pulse-shape analysis of HPGe detectors

    Science.gov (United States)

    Martín, S.; Quintana, B.; Barrientos, D.

    2016-07-01

    The characterization of the electric response of segmented-contact high-purity germanium detectors requires scanning systems capable of accurately associating each pulse with the position of the interaction that generated it. This process requires an algorithm sensitive to changes above the electronic noise in the pulse shapes produced at different positions, depending on the resolution of the Ge crystal. In this work, a pulse-shape comparison technique based on the Wilcoxon signed-rank test has been developed. It provides a method to distinguish pulses coming from different interaction points in the germanium crystal. Therefore, this technique is a necessary step for building a reliable pulse-shape database that can be used later for the determination of the position of interaction for γ-ray tracking spectrometry devices such as AGATA, GRETA or GERDA. The method was validated by comparison with a χ2 test using simulated and experimental pulses corresponding to a Broad Energy germanium detector (BEGe).

  1. Wilcoxon signed-rank-based technique for the pulse-shape analysis of HPGe detectors

    International Nuclear Information System (INIS)

    Martín, S.; Quintana, B.; Barrientos, D.

    2016-01-01

    The characterization of the electric response of segmented-contact high-purity germanium detectors requires scanning systems capable of accurately associating each pulse with the position of the interaction that generated it. This process requires an algorithm sensitive to changes above the electronic noise in the pulse shapes produced at different positions, depending on the resolution of the Ge crystal. In this work, a pulse-shape comparison technique based on the Wilcoxon signed-rank test has been developed. It provides a method to distinguish pulses coming from different interaction points in the germanium crystal. Therefore, this technique is a necessary step for building a reliable pulse-shape database that can be used later for the determination of the position of interaction for γ-ray tracking spectrometry devices such as AGATA, GRETA or GERDA. The method was validated by comparison with a χ"2 test using simulated and experimental pulses corresponding to a Broad Energy germanium detector (BEGe).

  2. A rank-based sequence aligner with applications in phylogenetic analysis.

    Directory of Open Access Journals (Sweden)

    Liviu P Dinu

    Full Text Available Recent tools for aligning short DNA reads have been designed to optimize the trade-off between correctness and speed. This paper introduces a method for assigning a set of short DNA reads to a reference genome, under Local Rank Distance (LRD. The rank-based aligner proposed in this work aims to improve correctness over speed. However, some indexing strategies to speed up the aligner are also investigated. The LRD aligner is improved in terms of speed by storing [Formula: see text]-mer positions in a hash table for each read. Another improvement, that produces an approximate LRD aligner, is to consider only the positions in the reference that are likely to represent a good positional match of the read. The proposed aligner is evaluated and compared to other state of the art alignment tools in several experiments. A set of experiments are conducted to determine the precision and the recall of the proposed aligner, in the presence of contaminated reads. In another set of experiments, the proposed aligner is used to find the order, the family, or the species of a new (or unknown organism, given only a set of short Next-Generation Sequencing DNA reads. The empirical results show that the aligner proposed in this work is highly accurate from a biological point of view. Compared to the other evaluated tools, the LRD aligner has the important advantage of being very accurate even for a very low base coverage. Thus, the LRD aligner can be considered as a good alternative to standard alignment tools, especially when the accuracy of the aligner is of high importance. Source code and UNIX binaries of the aligner are freely available for future development and use at http://lrd.herokuapp.com/aligners. The software is implemented in C++ and Java, being supported on UNIX and MS Windows.

  3. A Third-Rank Tensor Field Based on a U(1) Gauge Theory in Loop Space

    OpenAIRE

    Shinichi, DEGUCHI; Tadahito, NAKAJIMA; Department of Physics and Atomic Energy Research Institute College of Science and Technology; Department of Physics and Atomic Energy Research Institute College of Science and Technology

    1995-01-01

    We derive the Stueckelberg formalism extended to a third-rank tensor field from a U(1) gauge theory in loop space, the space of all loops in space-time. The third-rank tensor field is regarded as a constrained U(1) gauge field on the loop space.

  4. DEA ranking of municipalities of the Republic of Serbia based on efficiency of SMEs in agribusiness

    Directory of Open Access Journals (Sweden)

    Maletić Radojka

    2015-01-01

    Full Text Available The most important aspect of any business is efficiency. The goal is to achieve a greater output results using less inputs, i.e. to maximize the use of available inputs. Numerous mathematical and statistical procedures, such as DEA technique (Data Envelopment Analysis, take an important place in the process of the effective management of the company and its business activities. This paper illustrated the application of DEA technique in assessing the business efficiency of SMEs in agribusiness in Vojvodina Measuring the efficiency of business operations of SMEs is based on the values of the following indicators: fixed assets, working capital, number of companies, number of employees, total income, profit and loss. The data used to calculate the values of indicators of business efficiency were obtained from the Statistical Office of the Republic of Serbia, based on the annual accounts of SMEs in agribusiness for four-year average (2008-2011. The aim of this paper is statistical assessment of business efficiency of SMEs in agribusiness using DEA technique, and then, based on the results obtained, to perform the ranking of Vojvodina municipalities in which observed SMEs were located, and finally, based on 4 models, to show sensitivity of DEA technique compared to different combination of input / output indicators, so therefore, caution is needed when this method is used. If the combination of parameters in the model is better, the results are more realistic, since if a key parameter is omitted, wrong decisions could be made.

  5. Modern Resource-Based Theory(ies)

    DEFF Research Database (Denmark)

    Foss, Nicolai Juul; Stieglitz, Nils

    We survey the resource-based view in strategic management, focusing on its roots in economics. We organize our discussion in terms of the Gavetti and Levinthal distinction between a “high church” and a “low church” resource-based view, and argue that these hitherto rather separate streams...

  6. Research Ranking of Iranian Universities of Medical Sciences Based on International Indicators: An Experience From I.R. of Iran.

    Science.gov (United States)

    Baradaran Eftekhari, Monir; Sobhani, Zahra; Eltemasi, Masoumeh; Ghalenoee, Elham; Falahat, Katayoun; Habibi, Elham; Djalalinia, Shirin; Paykari, Niloofar; Ebadifar, Asghar; Akhondzadeh, Shahin

    2017-11-01

    In recent years, international ranking systems have been used by diverse users for various purposes. In most of these rankings, different aspects of performance of universities and research institutes, especially scientific performance, have been evaluated and ranked. In this article, we aimed to report the results of research ranking of Iranian universities of medical sciences (UMSs) based on some international indicators in 2015. In this study, after reviewing the research indicators of the majority of international ranking systems, with the participation of key stakeholders, we selected eight research indicators, namely research output, high-quality publications, leadership, total citations, citations per paper in 2015, papers per faculty member and h-index. The main sources for data gathering were Scopus, PubMed, and ISI, Web of Science. Data were extracted and normalized for Iranian governmental UMSs for 2015. A total of 18023 articles were indexed in 2015 in Scopus with affiliations of UMSs affiliation. Almost 17% of all articles were published in top journals and 15% were published with international collaborations. The maximum h-index (h-index = 110) belonged to Tehran University of Medical Sciences. The average paper per faculty member was 1.14 (Max = 2.5, Min = 0.13). The mean citation per published articles in Scopus was 0.33. Research ranking of Iranian UMSs can create favorable competition among them towards knowledge production.

  7. Ranking scientific publications: the effect of nonlinearity

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

    2014-10-01

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  8. Ranking scientific publications: the effect of nonlinearity.

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru

    2014-10-17

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  9. Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach.

    Science.gov (United States)

    Chen, Jinying; Jagannatha, Abhyuday N; Fodeh, Samah J; Yu, Hong

    2017-10-31

    Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation-that is, creating lay definitions for these terms. Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target

  10. Efficient Multi-keyword Ranked Search over Outsourced Cloud Data based on Homomorphic Encryption

    Directory of Open Access Journals (Sweden)

    Nie Mengxi

    2016-01-01

    Full Text Available With the development of cloud computing, more and more data owners are motivated to outsource their data to the cloud server for great flexibility and less saving expenditure. Because the security of outsourced data must be guaranteed, some encryption methods should be used which obsoletes traditional data utilization based on plaintext, e.g. keyword search. To solve the search of encrypted data, some schemes were proposed to solve the search of encrypted data, e.g. top-k single or multiple keywords retrieval. However, the efficiency of these proposed schemes is not high enough to be impractical in the cloud computing. In this paper, we propose a new scheme based on homomorphic encryption to solve this challenging problem of privacy-preserving efficient multi-keyword ranked search over outsourced cloud data. In our scheme, the inner product is adopted to measure the relevance scores and the technique of relevance feedback is used to reflect the search preference of the data users. Security analysis shows that the proposed scheme can meet strict privacy requirements for such a secure cloud data utilization system. Performance evaluation demonstrates that the proposed scheme can achieve low overhead on both computation and communication.

  11. A heuristic ranking approach on capacity benefit margin determination using Pareto-based evolutionary programming technique.

    Science.gov (United States)

    Othman, Muhammad Murtadha; Abd Rahman, Nurulazmi; Musirin, Ismail; Fotuhi-Firuzabad, Mahmud; Rajabi-Ghahnavieh, Abbas

    2015-01-01

    This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  12. A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique

    Directory of Open Access Journals (Sweden)

    Muhammad Murtadha Othman

    2015-01-01

    Full Text Available This paper introduces a novel multiobjective approach for capacity benefit margin (CBM assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE in various conditions. Eventually, the power transfer based available transfer capability (ATC is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.

  13. Ranking Adverse Drug Reactions With Crowdsourcing

    KAUST Repository

    Gottlieb, Assaf

    2015-03-23

    Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  14. Ranking adverse drug reactions with crowdsourcing.

    Science.gov (United States)

    Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

    2015-03-23

    There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  15. A comparison of sequential and information-based methods for determining the co-integration rank in heteroskedastic VAR MODELS

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Angelis, Luca De; Rahbek, Anders

    2015-01-01

    In this article, we investigate the behaviour of a number of methods for estimating the co-integration rank in VAR systems characterized by heteroskedastic innovation processes. In particular, we compare the efficacy of the most widely used information criteria, such as Akaike Information Criterion....... The relative finite-sample properties of the different methods are investigated by means of a Monte Carlo simulation study. For the simulation DGPs considered in the analysis, we find that the BIC-based procedure and the bootstrap sequential test procedure deliver the best overall performance in terms......-based method to over-estimate the co-integration rank in relatively small sample sizes....

  16. A comprehensive physiologically based pharmacokinetic knowledgebase and web-based interface for rapid model ranking and querying

    Science.gov (United States)

    Published physiologically based pharmacokinetic (PBPK) models from peer-reviewed articles are often well-parameterized, thoroughly-vetted, and can be utilized as excellent resources for the construction of models pertaining to related chemicals. Specifically, chemical-specific pa...

  17. Ranking multiple docking solutions based on the conservation of inter-residue contacts

    KAUST Repository

    Oliva, Romina M.; Vangone, Anna; Cavallo, Luigi

    2013-01-01

    ) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First

  18. Ranking alternatives based on imprecise multi-criteria data and pairwise overlap dominance relations

    DEFF Research Database (Denmark)

    Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt

    illustrative example is given for comparison with standard methods like PROMETHEE. The proposed methodology takes into account the risk attitudes of decision makers, organizing the alternatives and ranking them according to their relevance. The whole interactive decision support allows understanding...

  19. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

    Directory of Open Access Journals (Sweden)

    Yubao Sun

    2015-01-01

    Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

  1. Construction Cost Management in Resource Based Economy

    OpenAIRE

    Elazzazy, Muhammad

    2017-01-01

    Resource Based Economy tested according to criteria formulated from the construction cost management best practices. A cost management plan modeled to demonstrate the possibility of construction management under a new socio-economic system, which counts the consumed natural resources by construction as the dry cost to the environment.

  2. PageRank-based identification of signaling crosstalk from transcriptomics data: the case of Arabidopsis thaliana.

    Science.gov (United States)

    Omranian, Nooshin; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2012-04-01

    The levels of cellular organization, from gene transcription to translation to protein-protein interaction and metabolism, operate via tightly regulated mutual interactions, facilitating organismal adaptability and various stress responses. Characterizing the mutual interactions between genes, transcription factors, and proteins involved in signaling, termed crosstalk, is therefore crucial for understanding and controlling cells' functionality. We aim at using high-throughput transcriptomics data to discover previously unknown links between signaling networks. We propose and analyze a novel method for crosstalk identification which relies on transcriptomics data and overcomes the lack of complete information for signaling pathways in Arabidopsis thaliana. Our method first employs a network-based transformation of the results from the statistical analysis of differential gene expression in given groups of experiments under different signal-inducing conditions. The stationary distribution of a random walk (similar to the PageRank algorithm) on the constructed network is then used to determine the putative transcripts interrelating different signaling pathways. With the help of the proposed method, we analyze a transcriptomics data set including experiments from four different stresses/signals: nitrate, sulfur, iron, and hormones. We identified promising gene candidates, downstream of the transcription factors (TFs), associated to signaling crosstalk, which were validated through literature mining. In addition, we conduct a comparative analysis with the only other available method in this field which used a biclustering-based approach. Surprisingly, the biclustering-based approach fails to robustly identify any candidate genes involved in the crosstalk of the analyzed signals. We demonstrate that our proposed method is more robust in identifying gene candidates involved downstream of the signaling crosstalk for species for which large transcriptomics data sets

  3. Ranking system for national regulatory jurisdictions based on pesticide standard values in major exposures

    Directory of Open Access Journals (Sweden)

    Zijian Li

    2017-07-01

    Full Text Available To control the risk of human exposure to pesticides, about 50 nations have promulgated pesticide soil regulatory guidance values (RGVs, and 104 nations have provided pesticide drinking water maximum concentration levels (MCLs. In addition, 90 nations have regulated pesticide agricultural commodity maximum residue limits (MRLs. Pesticide standard values (PSVs for one single pesticide varied in a range of six, seven, or even eight orders of magnitude. Some PSVs are too large to prevent the impact of pesticides on human health. Many nations have not provided PSVs for some commonly used pesticides until now. This research has introduced several completeness values and numerical values methods to evaluate the national jurisdiction’s performance on PSVs on a nation base. The national jurisdiction ranking system developed by these methods will be beneficial to the environmental regulation makers in the management of PSVs. Results also indicate that European countries perform better in the regulation of pesticide soil RGVs, drinking water MCLs, and agricultural commodity MRLs.

  4. Data depth and rank-based tests for covariance and spectral density matrices

    KAUST Repository

    Chau, Joris

    2017-06-26

    In multivariate time series analysis, objects of primary interest to study cross-dependences in the time series are the autocovariance or spectral density matrices. Non-degenerate covariance and spectral density matrices are necessarily Hermitian and positive definite, and our primary goal is to develop new methods to analyze samples of such matrices. The main contribution of this paper is the generalization of the concept of statistical data depth for collections of covariance or spectral density matrices by exploiting the geometric properties of the space of Hermitian positive definite matrices as a Riemannian manifold. This allows one to naturally characterize most central or outlying matrices, but also provides a practical framework for rank-based hypothesis testing in the context of samples of covariance or spectral density matrices. First, the desired properties of a data depth function acting on the space of Hermitian positive definite matrices are presented. Second, we propose two computationally efficient pointwise and integrated data depth functions that satisfy each of these requirements. Several applications of the developed methodology are illustrated by the analysis of collections of spectral matrices in multivariate brain signal time series datasets.

  5. Rank-based permutation approaches for non-parametric factorial designs.

    Science.gov (United States)

    Umlauft, Maria; Konietschke, Frank; Pauly, Markus

    2017-11-01

    Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

  6. Web-based tool for subjective observer ranking of compressed medical images

    Science.gov (United States)

    Langer, Steven G.; Stewart, Brent K.; Andrew, Rex K.

    1999-05-01

    In the course of evaluating various compression schemes for ultrasound teleradiology applications, it became obvious that paper based methods of data collection were time consuming and error prone. A method was sought which allowed participating radiologists to view the ultrasound video clips (compressed to varying degree) at their desks. Furthermore, the method should allow observers to enter their evaluations and when finished, automatically submit the data to our statistical analysis engine. We have found the World Wide Web offered a ready solution. A web page was constructed that contains 18 embedded AVI video clips. The 18 clips represent 6 distinct anatomical areas, compressed by various methods and amounts, and then randomly distributed through the web page. To the right of each video, a series of questions are presented which ask the observer to rank (1 - 5) his/her ability to answer diagnostically relevant questions. When completed, the observer presses 'Submit' and a file of tab delimited test is created which can then be imported to an Excel workbook. Kappa analysis is then performed and the resulting plots demonstrate observer preferences.

  7. Rank-Based miRNA Signatures for Early Cancer Detection

    Directory of Open Access Journals (Sweden)

    Mario Lauria

    2014-01-01

    Full Text Available We describe a new signature definition and analysis method to be used as biomarker for early cancer detection. Our new approach is based on the construction of a reference map of transcriptional signatures of both healthy and cancer affected individuals using circulating miRNA from a large number of subjects. Once such a map is available, the diagnosis for a new patient can be performed by observing the relative position on the map of his/her transcriptional signature. To demonstrate its efficacy for this specific application we report the results of the application of our method to published datasets of circulating miRNA, and we quantify its performance compared to current state-of-the-art methods. A number of additional features make this method an ideal candidate for large-scale use, for example, as a mass screening tool for early cancer detection or for at-home diagnostics. Specifically, our method is minimally invasive (because it works well with circulating miRNA, it is robust with respect to lab-to-lab protocol variability and batch effects (it requires that only the relative ranking of expression value of miRNA in a profile be accurate not their absolute values, and it is scalable to a large number of subjects. Finally we discuss the need for HPC capability in a widespread application of our or similar methods.

  8. Wilcoxon signed-rank-based technique for the pulse-shape analysis of HPGe detectors

    Energy Technology Data Exchange (ETDEWEB)

    Martín, S., E-mail: sergiomr@usal.es; Quintana, B.; Barrientos, D.

    2016-07-01

    The characterization of the electric response of segmented-contact high-purity germanium detectors requires scanning systems capable of accurately associating each pulse with the position of the interaction that generated it. This process requires an algorithm sensitive to changes above the electronic noise in the pulse shapes produced at different positions, depending on the resolution of the Ge crystal. In this work, a pulse-shape comparison technique based on the Wilcoxon signed-rank test has been developed. It provides a method to distinguish pulses coming from different interaction points in the germanium crystal. Therefore, this technique is a necessary step for building a reliable pulse-shape database that can be used later for the determination of the position of interaction for γ-ray tracking spectrometry devices such as AGATA, GRETA or GERDA. The method was validated by comparison with a χ{sup 2} test using simulated and experimental pulses corresponding to a Broad Energy germanium detector (BEGe).

  9. Data depth and rank-based tests for covariance and spectral density matrices

    KAUST Repository

    Chau, Joris; Ombao, Hernando; Sachs, Rainer von

    2017-01-01

    In multivariate time series analysis, objects of primary interest to study cross-dependences in the time series are the autocovariance or spectral density matrices. Non-degenerate covariance and spectral density matrices are necessarily Hermitian and positive definite, and our primary goal is to develop new methods to analyze samples of such matrices. The main contribution of this paper is the generalization of the concept of statistical data depth for collections of covariance or spectral density matrices by exploiting the geometric properties of the space of Hermitian positive definite matrices as a Riemannian manifold. This allows one to naturally characterize most central or outlying matrices, but also provides a practical framework for rank-based hypothesis testing in the context of samples of covariance or spectral density matrices. First, the desired properties of a data depth function acting on the space of Hermitian positive definite matrices are presented. Second, we propose two computationally efficient pointwise and integrated data depth functions that satisfy each of these requirements. Several applications of the developed methodology are illustrated by the analysis of collections of spectral matrices in multivariate brain signal time series datasets.

  10. Sustainability Investigation of Resource-Based Cities in Northeastern China

    Directory of Open Access Journals (Sweden)

    Chengpeng Lu

    2016-10-01

    Full Text Available Improving the sustainability of traditional resource-based cities in China has been a core issue and policy-priority for Chinese government to establish long-term ecological civilization, particularly for northeastern China which is recognized as a typical agglomeration area of resources cities. In this study, we establish a three-layer index system consisting of a comprehensive layer, systemic layer, and variable layer, and including 22 indicators which are grouped into economic, social and environmental subsystems. After that, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution method was applied to measure and rank the sustainability of the selected 15 typical resource-based cities in northeast China, and then a GIS (Geographical Information System technique based on the software of SuperMap was applied to map the sustainability in terms of the spatial effects among these cities. The results reveal that a unilateral improvement of a subsystem did not mean an improvement or contribution to whole system. In detail, during the past 15 years from 2000 to 2015, the comprehensive sustainability of resource-based cities in Northeastern China shows a declining trend in the mass, and the sustainability of the economic subsystem shows increase; the sustainability of the social system remains stable, while the environmental subsystem shows decrease. These situations might result from policy interventions during the past 15 years, therefore, promoting the sustainability of resource-based cities needs a historical approach, which should focus on the coordinated development of its economic, social, and environmental subsystems.

  11. Microseismic Event Relocation and Focal Mechanism Estimation Based on PageRank Linkage

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2017-12-01

    Microseismicity associated with enhanced geothermal systems (EGS) is key in understanding how subsurface stimulation can modify stress, fracture rock, and increase permeability. Large numbers of microseismic events are commonly associated with hydroshearing an EGS, making data mining methods useful in their analysis. We focus on PageRank, originally developed as Google's search engine, and subsequently adapted for use in seismology to detect low-frequency earthquakes by linking events directly and indirectly through cross-correlation (Aguiar and Beroza, 2014). We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes from the Newberry Volcano EGS in Central Oregon, which has been stimulated two times using high-pressure fluid injection. We create PageRank signal families from both data sets and compare these to the spatial and temporal proximity of associated earthquakes. PageRank families are relocated using differential travel times measured by waveform cross-correlation (CC) and the Bayesloc approach (Myers et al., 2007). Prior to relocation events are loosely clustered with events at a distance from the cluster. After relocation, event families are found to be tightly clustered. Indirect linkage of signals using PageRank is a reliable way to increase the number of events confidently determined to be similar, suggesting an efficient and effective grouping of earthquakes with similar physical characteristics (ie. location, focal mechanism, stress drop). We further explore the possibility of using PageRank families to identify events with similar relative phase polarities and estimate focal mechanisms following Shelly et al. (2016) method, where CC measurements are used to determine individual polarities within event clusters. Given a positive result, PageRank might be a useful tool in adaptive approaches to enhance production at well-instrumented geothermal sites. Prepared by LLNL under Contract DE-AC52-07NA27344

  12. The optimized expansion based low-rank method for wavefield extrapolation

    KAUST Repository

    Wu, Zedong

    2014-03-01

    Spectral methods are fast becoming an indispensable tool for wavefield extrapolation, especially in anisotropic media because it tends to be dispersion and artifact free as well as highly accurate when solving the wave equation. However, for inhomogeneous media, we face difficulties in dealing with the mixed space-wavenumber domain extrapolation operator efficiently. To solve this problem, we evaluated an optimized expansion method that can approximate this operator with a low-rank variable separation representation. The rank defines the number of inverse Fourier transforms for each time extrapolation step, and thus, the lower the rank, the faster the extrapolation. The method uses optimization instead of matrix decomposition to find the optimal wavenumbers and velocities needed to approximate the full operator with its explicit low-rank representation. As a result, we obtain lower rank representations compared with the standard low-rank method within reasonable accuracy and thus cheaper extrapolations. Additional bounds set on the range of propagated wavenumbers to adhere to the physical wave limits yield unconditionally stable extrapolations regardless of the time step. An application on the BP model provided superior results compared to those obtained using the decomposition approach. For transversely isotopic media, because we used the pure P-wave dispersion relation, we obtained solutions that were free of the shear wave artifacts, and the algorithm does not require that n > 0. In addition, the required rank for the optimization approach to obtain high accuracy in anisotropic media was lower than that obtained by the decomposition approach, and thus, it was more efficient. A reverse time migration result for the BP tilted transverse isotropy model using this method as a wave propagator demonstrated the ability of the algorithm.

  13. WTS - Risk Based Resource Targeting (RBRT) -

    Data.gov (United States)

    Department of Transportation — The Risk Based Resource Targeting (RBRT) application supports a new SMS-structured process designed to focus on safety oversight of systems and processes rather than...

  14. RANKING OF COMPANIES ACCORDING TO THE INDICATORS OF CORPORATE SOCIAL RESPONSIBILITY BASED ON SWARA AND ARAS METHODS

    Directory of Open Access Journals (Sweden)

    Darjan Karabasevic

    2016-05-01

    Full Text Available Corporate sector and companies have recognized the importance of implementation of strategy of corporate social responsibility in order to increase the company's image and responsibility towards society and the communities where they operate. Multinational companies in their everyday activities and operations pay more attention to sustainable models of corporate social responsibility. The focus of this paper is to identify the indicators of corporate social responsibility and to rank companies according to the indicators. Proposed framework for evaluation and ranking is based on the SWARA and the ARAS methods. The usability and efficiency of the proposed framework is shown on an illustrative example.

  15. Selection and ranking of occupational safety indicators based on fuzzy AHP: A case study in road construction companies

    Directory of Open Access Journals (Sweden)

    Janackovic, Goran Lj.

    2013-11-01

    Full Text Available This paper presents the factors, performance, and indicators of occupational safety, as well as a method to select and rank occupational safety indicators based on the expert evaluation method and the fuzzy analytic hierarchy process (fuzzy AHP. A case study is done on road construction companies in Serbia. The key safety performance indicators for the road construction industry are identified and ranked according to the results of a survey that included experts who assessed occupational safety risks in these companies. The case study confirmed that organisational factors have a dominant effect on the quality of the occupational health and safety management system in Serbian road construction companies.

  16. A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion.

    Science.gov (United States)

    Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit

    2017-05-01

    Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.

  17. Dose-volume based ranking of incident beam direction and its utility in facilitating IMRT beam placement

    International Nuclear Information System (INIS)

    Schreibmann, Eduard; Xing Lei

    2005-01-01

    Purpose: Beam orientation optimization in intensity-modulated radiation therapy (IMRT) is computationally intensive, and various single beam ranking techniques have been proposed to reduce the search space. Up to this point, none of the existing ranking techniques considers the clinically important dose-volume effects of the involved structures, which may lead to clinically irrelevant angular ranking. The purpose of this work is to develop a clinically sensible angular ranking model with incorporation of dose-volume effects and to show its utility for IMRT beam placement. Methods and Materials: The general consideration in constructing this angular ranking function is that a beamlet/beam is preferable if it can deliver a higher dose to the target without exceeding the tolerance of the sensitive structures located on the path of the beamlet/beam. In the previously proposed dose-based approach, the beamlets are treated independently and, to compute the maximally deliverable dose to the target volume, the intensity of each beamlet is pushed to its maximum intensity without considering the values of other beamlets. When volumetric structures are involved, the complication arises from the fact that there are numerous dose distributions corresponding to the same dose-volume tolerance. In this situation, the beamlets are not independent and an optimization algorithm is required to find the intensity profile that delivers the maximum target dose while satisfying the volumetric constraints. In this study, the behavior of a volumetric organ was modeled by using the equivalent uniform dose (EUD). A constrained sequential quadratic programming algorithm (CFSQP) was used to find the beam profile that delivers the maximum dose to the target volume without violating the EUD constraint or constraints. To assess the utility of the proposed technique, we planned a head-and-neck and abdominal case with and without the guidance of the angular ranking information. The qualities of the

  18. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse; Petta, A.; Serra, L.; Vangone, A.; Scarano, V.; Cavallo, Luigi; Oliva, R.

    2014-01-01

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  19. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse

    2014-12-21

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  20. Methodological Bases for Ranking the European Union Countries in Terms of Macroeconomic Security

    Directory of Open Access Journals (Sweden)

    Tymoshenko Olena V.

    2015-11-01

    Full Text Available The fundamental contradictions of existing methodical approaches to assessing the level of the state economic security have been substantiated and proposals on the introduction of a unified methodology for its assessment, which would be acceptable for use at the international level or for a specific cluster of countries, have been developed. Based on the conducted researches it has been found that the there are no unified signs for such classification of countries. To determine the most significant coefficients and critical values of the indicators of economic security, it is appropriate that the countries should be grouped in terms of the level of the economic development proposed by the UN Commission and the IMF. Analysis of the economic security level has been conducted for the countries-members of the European Union as a separate cluster of countries on the example of macroeconomic security indicators. Based on the evaluation it has been found that the proposed list of indicators and their critical values is economically sound and built on the principle of adequacy, representativeness and comprehensiveness. In 2004 the most secure countries of the EU corresponding to the macroeconomic security standards were Austria, Denmark, Sweden, Finland, and as in 2014 the percentage of absolutely secure countries decreased from 14.3 to 7.1%, only Denmark and Sweden remained in the ranking. During the analyzed period Bulgaria and Croatia got into the risk zone, Estonia, Lithuania, Latvia, Romania were in a danger zone. In 2014 Ukraine in terms of its macroeconomic security was in a critical state, which testified about serious structural and system imbalances in its development.

  1. Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition.

    Science.gov (United States)

    Lu, Lijun; Ma, Xiaomian; Mohy-Ud-Din, Hassan; Ma, Jianhua; Feng, Qianjin; Rahmim, Arman; Chen, Wufan

    2018-02-01

    The absolute quantification of dynamic myocardial perfusion (MP) PET imaging is challenged by the limited spatial resolution of individual frame images due to division of the data into shorter frames. This study aims to develop a method for restoration and enhancement of dynamic PET images. We propose that the image restoration model should be based on multiple constraints rather than a single constraint, given the fact that the image characteristic is hardly described by a single constraint alone. At the same time, it may be possible, but not optimal, to regularize the image with multiple constraints simultaneously. Fortunately, MP PET images can be decomposed into a superposition of background vs. dynamic components via low-rank plus sparse (L + S) decomposition. Thus, we propose an L + S decomposition based MP PET image restoration model and express it as a convex optimization problem. An iterative soft thresholding algorithm was developed to solve the problem. Using realistic dynamic 82 Rb MP PET scan data, we optimized and compared its performance with other restoration methods. The proposed method resulted in substantial visual as well as quantitative accuracy improvements in terms of noise versus bias performance, as demonstrated in extensive 82 Rb MP PET simulations. In particular, the myocardium defect in the MP PET images had improved visual as well as contrast versus noise tradeoff. The proposed algorithm was also applied on an 8-min clinical cardiac 82 Rb MP PET study performed on the GE Discovery PET/CT, and demonstrated improved quantitative accuracy (CNR and SNR) compared to other algorithms. The proposed method is effective for restoration and enhancement of dynamic PET images. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. How to Rank Journals.

    Science.gov (United States)

    Bradshaw, Corey J A; Brook, Barry W

    2016-01-01

    There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

  3. Ranking of Prokaryotic Genomes Based on Maximization of Sortedness of Gene Lengths.

    Science.gov (United States)

    Bolshoy, A; Salih, B; Cohen, I; Tatarinova, T

    How variations of gene lengths (some genes become longer than their predecessors, while other genes become shorter and the sizes of these factions are randomly different from organism to organism) depend on organismal evolution and adaptation is still an open question. We propose to rank the genomes according to lengths of their genes, and then find association between the genome rank and variousproperties, such as growth temperature, nucleotide composition, and pathogenicity. This approach reveals evolutionary driving factors. The main purpose of this study is to test effectiveness and robustness of several ranking methods. The selected method of evaluation is measuring of overall sortedness of the data. We have demonstrated that all considered methods give consistent results and Bubble Sort and Simulated Annealing achieve the highest sortedness. Also, Bubble Sort is considerably faster than the Simulated Annealing method.

  4. Ranking provinces based on development scale in agriculture sector using taxonomy technique

    Directory of Open Access Journals (Sweden)

    Shahram Rostampour

    2012-08-01

    Full Text Available The purpose of this paper is to determine comparative ranking of agricultural development in different provinces of Iran using taxonomy technique. The independent variables are amount of annual rainfall amount, the number of permanent rivers, the width of pastures and forest, cultivated level of agricultural harvests and garden harvests, number of beehives, the number of fish farming ranches, the number of tractors and combines, the number of cooperative production societies, the number of industrial cattle breeding and aviculture. The results indicate that the maximum development coefficient value is associated with Razavi Khorasan province followed by Mazandaran, East Azarbayjan while the minimum ranking value belongs to Bushehr province.

  5. Strategy community development based on local resources

    Science.gov (United States)

    Meirinawati; Prabawati, I.; Pradana, G. W.

    2018-01-01

    The problem of progressing regions is not far from economic problems and is often caused by the inability of the regions in response to changes in economic conditions that occur, so the need for community development programs implemented to solve various problems. Improved community effort required with the real conditions and needs of each region. Community development based on local resources process is very important, because it is an increase in human resource capability in the optimal utilization of local resource potential. In this case a strategy is needed in community development based on local resources. The community development strategy are as follows:(1) “Eight Line Equalization Plus” which explains the urgency of rural industrialization, (2) the construction of the village will be more successful when combining strategies are tailored to regional conditions, (3) the escort are positioning themselves as the Planner, supervisor, information giver, motivator, facilitator, connecting at once evaluators.

  6. Low-rank extremal positive-partial-transpose states and unextendible product bases

    International Nuclear Information System (INIS)

    Leinaas, Jon Magne; Sollid, Per Oyvind; Myrheim, Jan

    2010-01-01

    It is known how to construct, in a bipartite quantum system, a unique low-rank entangled mixed state with positive partial transpose (a PPT state) from an unextendible product basis (UPB), defined as an unextendible set of orthogonal product vectors. We point out that a state constructed in this way belongs to a continuous family of entangled PPT states of the same rank, all related by nonsingular unitary or nonunitary product transformations. The characteristic property of a state ρ in such a family is that its kernel Ker ρ has a generalized UPB, a basis of product vectors, not necessarily orthogonal, with no product vector in Im ρ, the orthogonal complement of Ker ρ. The generalized UPB in Ker ρ has the special property that it can be transformed to orthogonal form by a product transformation. In the case of a system of dimension 3x3, we give a complete parametrization of orthogonal UPBs. This is then a parametrization of families of rank 4 entangled (and extremal) PPT states, and we present strong numerical evidence that it is a complete classification of such states. We speculate that the lowest rank entangled and extremal PPT states also in higher dimensions are related to generalized, nonorthogonal UPBs in similar ways.

  7. A Distributed Taxation Based Rank Adaptation Scheme for 5G Small Cells

    DEFF Research Database (Denmark)

    Catania, Davide; Cattoni, Andrea Fabio; Mahmood, Nurul Huda

    2015-01-01

    The further densification of small cells impose high and undesirable levels of inter-cell interference. Multiple Input Multiple Output (MIMO) systems along with advanced receiver techniques provide us with extra degrees of freedom to combat such a problem. With such tools, rank adaptation...

  8. Stakeholder Perspectives on Citation and Peer-Based Rankings of Higher Education Journals

    Science.gov (United States)

    Wilkins, Stephen; Huisman, Jeroen

    2015-01-01

    The purpose of this article is to identify and discuss the possible uses of higher education journal rankings, and the associated advantages and disadvantages of using them. The research involved 40 individuals--lecturers, university managers, journal editors and publishers--who represented a range of stakeholders involved with research into…

  9. Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

    Science.gov (United States)

    He, Y.; Wang, X.; Hu, X. Y.; Liu, S. H.

    2018-04-01

    The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

  10. The assessment and the farmers' perceived ranking of feed resources and coping strategies with feed scarcity in smallholder dairy farming in selected district towns of Jimma Zone, Ethiopia.

    Science.gov (United States)

    Duguma, Belay; Dermauw, Veronique; Janssens, Geert

    2017-06-01

    Inadequate quantity and quality of feed resources are major constraints limiting milk production and reproductive performance of dairy cattle in Ethiopia. The aim of this study was to assess dairy cattle feed resources, feeding practices, the farmers' perceived ranking of feed resources, causes of feed shortage, and coping strategies to feed scarcity in smallholder dairy system in selected district towns of Jimma Zone, Ethiopia. Data were obtained by interviewing 52 randomly selected smallholder dairy farmers using structured questionnaires and through direct observations. Results showed that 20 main feed types used by dairy farmers were identified and categorized into natural pastures, crop residues, green feeds, hay, agro-industrial by-products, concentrate mix, and non-conventional feeds. Overall, natural pasture (mean rank = 0.453), non-conventional feeds (0.307), cut green feeds (0.086), conserved hay (0.076), crop residues (0.049), and concentrate feeds (0.029) were ranked as the main feed resources in decreasing order of importance. Natural pasture grazing (92.2% of the respondents), hay (35.6%), and green feeds (29.4%) were the most important conventional basal feeds used. Wheat bran (11.7% of the respondents) followed by commercial concentrate mix (9.4%), Noug seedcake (8.3%), grain (7.8%), and molasses (6.1%) were the concentrate supplements used. Overall, bulule-flour mill leftovers (67.2% of the farmers), bean and pea hulls (57.2%) and atella-local brew by-product (37.2%), enset (Ensete ventricosum, 34.4%), and sugarcane top (32.2%) were the non-conventional feeds available and used during feed scarcity. Barley and teff (Eragrostis teff) straws and maize and sorghum stovers were the main crop residues used in the dry seasons. Overall, 73.9, 12.2, 12.2, and 1.7% of the respondents practiced free grazing, zero grazing, semi-zero, and a combination of zero- and free-grazing systems, respectively. Over 84% of the respondents in the dry season and 50% in

  11. Ranking multiple docking solutions based on the conservation of inter-residue contacts

    KAUST Repository

    Oliva, Romina M.

    2013-06-17

    Molecular docking is the method of choice for investigating the molecular basis of recognition in a large number of functional protein complexes. However, correctly scoring the obtained docking solutions (decoys) to rank native-like (NL) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First it calculates a conservation rate for each inter-residue contact, then it ranks decoys according to their ability to match the more frequently observed contacts. We applied CONSRANK to 102 targets from three different benchmarks, RosettaDock, DOCKGROUND, and Critical Assessment of PRedicted Interactions (CAPRI). The method performs consistently well, both in terms of NL solutions ranked in the top positions and of values of the area under the receiver operating characteristic curve. Its ideal application is to solutions coming from different docking programs and procedures, as in the case of CAPRI targets. For all the analyzed CAPRI targets where a comparison is feasible, CONSRANK outperforms the CAPRI scorers. The fraction of NL solutions in the top ten positions in the RosettaDock, DOCKGROUND, and CAPRI benchmarks is enriched on average by a factor of 3.0, 1.9, and 9.9, respectively. Interestingly, CONSRANK is also able to specifically single out the high/medium quality (HMQ) solutions from the docking decoys ensemble: it ranks 46.2 and 70.8% of the total HMQ solutions available for the RosettaDock and CAPRI targets, respectively, within the top 20 positions. © 2013 Wiley Periodicals, Inc.

  12. Community-based natural resource management

    DEFF Research Database (Denmark)

    Treue, Thorsten; Nathan, Iben

    that deliver credible and easily accessible information. Checks and balances can be supported through civil society as well as the media. Finally, the private sector plays a key and potentially beneficial role in the harvest, transport and marketing of CBNRM products. Thus, dialogue partners should include......This technical note is the product of a long process of consultation with a wide range of resource persons who have over the years been involved in the Danish support to Community Based Natural Resource Management. It gives a brief introduction to community-based natural resource management (CBNRM...... from CBNRM will be useful when designing community-based climate adaptation strategies. Thus, this note is a contribution to an ongoing debate as well as a product of the long-standing experiences of Danida's environmental portfolio. CBNRM is not a stand-alone solution to secure poverty reduction...

  13. MEDRank: using graph-based concept ranking to index biomedical texts.

    Science.gov (United States)

    Herskovic, Jorge R; Cohen, Trevor; Subramanian, Devika; Iyengar, M Sriram; Smith, Jack W; Bernstam, Elmer V

    2011-06-01

    As the volume of biomedical text increases exponentially, automatic indexing becomes increasingly important. However, existing approaches do not distinguish central (or core) concepts from concepts that were mentioned in passing. We focus on the problem of indexing MEDLINE records, a process that is currently performed by highly trained humans at the National Library of Medicine (NLM). NLM indexers are assisted by a system called the Medical Text Indexer (MTI) that suggests candidate indexing terms. To improve the ability of MTI to select the core terms in MEDLINE abstracts. These core concepts are deemed to be most important and are designated as "major headings" by MEDLINE indexers. We introduce and evaluate a graph-based indexing methodology called MEDRank that generates concept graphs from biomedical text and then ranks the concepts within these graphs to identify the most important ones. We insert a MEDRank step into the MTI and compare MTI's output with and without MEDRank to the MEDLINE indexers' selected terms for a sample of 11,803 PubMed Central articles. We also tested whether human raters prefer terms generated by the MEDLINE indexers, MTI without MEDRank, and MTI with MEDRank for a sample of 36 PubMed Central articles. MEDRank improved recall of major headings designated by 30% over MTI without MEDRank (0.489 vs. 0.376). Overall recall was only slightly (6.5%) higher (0.490 vs. 0.460) as was F(2) (3%, 0.408 vs. 0.396). However, overall precision was 3.9% lower (0.268 vs. 0.279). Human raters preferred terms generated by MTI with MEDRank over terms generated by MTI without MEDRank (by an average of 1.00 more term per article), and preferred terms generated by MTI with MEDRank and the MEDLINE indexers at the same rate. The addition of MEDRank to MTI significantly improved the retrieval of core concepts in MEDLINE abstracts and more closely matched human expectations compared to MTI without MEDRank. In addition, MEDRank slightly improved overall recall

  14. Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis

    International Nuclear Information System (INIS)

    Kim, Kyungsang; Ye, Jong Chul; Son, Young Don; Cho, Zang Hee; Bresler, Yoram; Ra, Jong Beom

    2015-01-01

    Dynamic positron emission tomography (PET) is widely used to measure changes in the bio-distribution of radiopharmaceuticals within particular organs of interest over time. However, to retain sufficient temporal resolution, the number of photon counts in each time frame must be limited. Therefore, conventional reconstruction algorithms such as the ordered subset expectation maximization (OSEM) produce noisy reconstruction images, thus degrading the quality of the extracted time activity curves (TACs). To address this issue, many advanced reconstruction algorithms have been developed using various spatio-temporal regularizations. In this paper, we extend earlier results and develop a novel temporal regularization, which exploits the self-similarity of patches that are collected in dynamic images. The main contribution of this paper is to demonstrate that the correlation of patches can be exploited using a low-rank constraint that is insensitive to global intensity variations. The resulting optimization framework is, however, non-Lipschitz and non-convex due to the Poisson log-likelihood and low-rank penalty terms. Direct application of the conventional Poisson image deconvolution by an augmented Lagrangian (PIDAL) algorithm is, however, problematic due to its large memory requirements, which prevents its parallelization. Thus, we propose a novel optimization framework using the concave-convex procedure (CCCP) by exploiting the Legendre–Fenchel transform, which is computationally efficient and parallelizable. In computer simulation and a real in vivo experiment using a high-resolution research tomograph (HRRT) scanner, we confirm that the proposed algorithm can improve image quality while also extracting more accurate region of interests (ROI) based kinetic parameters. Furthermore, we show that the total reconstruction time for HRRT PET is significantly accelerated using our GPU implementation, which makes the algorithm very practical in clinical environments

  15. A collaborative filtering recommendation algorithm based on weighted SimRank and social trust

    Science.gov (United States)

    Su, Chang; Zhang, Butao

    2017-05-01

    Collaborative filtering is one of the most widely used recommendation technologies, but the data sparsity and cold start problem of collaborative filtering algorithms are difficult to solve effectively. In order to alleviate the problem of data sparsity in collaborative filtering algorithm, firstly, a weighted improved SimRank algorithm is proposed to compute the rating similarity between users in rating data set. The improved SimRank can find more nearest neighbors for target users according to the transmissibility of rating similarity. Then, we build trust network and introduce the calculation of trust degree in the trust relationship data set. Finally, we combine rating similarity and trust to build a comprehensive similarity in order to find more appropriate nearest neighbors for target user. Experimental results show that the algorithm proposed in this paper improves the recommendation precision of the Collaborative algorithm effectively.

  16. Microseismic Event Grouping Based on PageRank Linkage at the Newberry Volcano Geothermal Site

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2016-12-01

    The Newberry Volcano DOE FORGE site in Central Oregon has been stimulated two times using high-pressure fluid injection to study the Enhanced Geothermal Systems (EGS) technology. Several hundred microseismic events were generated during the first stimulation in the fall of 2012. Initial locations of this microseismicity do not show well defined subsurface structure in part because event location uncertainties are large (Foulger and Julian, 2013). We focus on this stimulation to explore the spatial and temporal development of microseismicity, which is key to understanding how subsurface stimulation modifies stress, fractures rock, and increases permeability. We use PageRank, Google's initial search algorithm, to determine connectivity within the events (Aguiar and Beroza, 2014) and assess signal-correlation topology for the micro-earthquakes. We then use this information to create signal families and compare these to the spatial and temporal proximity of associated earthquakes. We relocate events within families (identified by PageRank linkage) using the Bayesloc approach (Myers et al., 2007). Preliminary relocations show tight spatial clustering of event families as well as evidence of events relocating to a different cluster than originally reported. We also find that signal similarity (linkage) at several stations, not just one or two, is needed in order to determine that events are in close proximity to one another. We show that indirect linkage of signals using PageRank is a reliable way to increase the number of events that are confidently determined to be similar to one another, which may lead to efficient and effective grouping of earthquakes with similar physical characteristics, such as focal mechanisms and stress drop. Our ultimate goal is to determine whether changes in the state of stress and/or changes in the generation of subsurface fracture networks can be detected using PageRank topology as well as aid in the event relocation to obtain more accurate

  17. AN EXCEL-BASED DECISION SUPPORT SYSTEM FOR SCORING AND RANKING PROPOSED R&D PROJECTS

    OpenAIRE

    ANNE DE PIANTE HENRIKSEN; SUSAN W. PALOCSAY

    2008-01-01

    One of the most challenging aspects of technology management is the selection of research and development (R&D) projects from among a group of proposals. This paper introduces an interactive, user-friendly decision support system for evaluating and ranking R&D projects and demonstrates its application on an example R&D program. It employs the scoring methodology developed by Henriksen and Traynor to provide a practical technique that considers both project merit and project cost in the evalua...

  18. Study on the feature of the Fortune 500 and the enlightenment basing on the 2014 ranking

    OpenAIRE

    Xue, Mingyue; Zhang, Zhifeng

    2015-01-01

    The world’s 500 biggest companies have drawn more and more attention since the journal Fortune started the ranking, Summarize the law of development of the world top 500 enterprises to develop China's enterprises has an important reference and enlightenment function. This paper carries on an overall analysis of the world’s 500 biggest companies, summarizes the shortcomings of Chinese largest companies and offers suggestions to the process and strategy towards the world’s 500 for Chinese enter...

  19. Color correction with blind image restoration based on multiple images using a low-rank model

    Science.gov (United States)

    Li, Dong; Xie, Xudong; Lam, Kin-Man

    2014-03-01

    We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

  20. Ranked solutions to a class of combinatorial optimizations - with applications in mass spectrometry based peptide sequencing

    Science.gov (United States)

    Doerr, Timothy; Alves, Gelio; Yu, Yi-Kuo

    2006-03-01

    Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time. This suggests a way to efficiently find approximate solutions - - find a transformation that makes the cost function as similar as possible to that of the solvable class. After keeping many high-ranking solutions using the approximate cost function, one may then re-assess these solutions with the full cost function to find the best approximate solution. Under this approach, it is important to be able to assess the quality of the solutions obtained, e.g., by finding the true ranking of kth best approximate solution when all possible solutions are considered exhaustively. To tackle this statistical issue, we provide a systematic method starting with a scaling function generated from the fininte number of high- ranking solutions followed by a convergent iterative mapping. This method, useful in a variant of the directed paths in random media problem proposed here, can also provide a statistical significance assessment for one of the most important proteomic tasks - - peptide sequencing using tandem mass spectrometry data.

  1. Ranking REACH registered neutral, ionizable and ionic organic chemicals based on their aquatic persistency and mobility.

    Science.gov (United States)

    Arp, H P H; Brown, T N; Berger, U; Hale, S E

    2017-07-19

    The contaminants that have the greatest chances of appearing in drinking water are those that are mobile enough in the aquatic environment to enter drinking water sources and persistent enough to survive treatment processes. Herein a screening procedure to rank neutral, ionizable and ionic organic compounds for being persistent and mobile organic compounds (PMOCs) is presented and applied to the list of industrial substances registered under the EU REACH legislation as of December 2014. This comprised 5155 identifiable, unique organic structures. The minimum cut-off criteria considered for PMOC classification herein are a freshwater half-life >40 days, which is consistent with the REACH definition of freshwater persistency, and a log D oc water distribution coefficient). Experimental data were given the highest priority, followed by data from an array of available quantitative structure-activity relationships (QSARs), and as a third resort, an original Iterative Fragment Selection (IFS) QSAR. In total, 52% of the unique REACH structures made the minimum criteria to be considered a PMOC, and 21% achieved the highest PMOC ranking (half-life > 40 days, log D oc freshwater persistency, which was also the parameter that QSARs performed the most poorly at predicting. Several prioritized drinking water contaminants in the EU and USA, and other contaminants of concern, were identified as PMOCs. This identification and ranking procedure for PMOCs can be part of a strategy to better identify contaminants that pose a threat to drinking water sources.

  2. University Rankings: The Web Ranking

    Science.gov (United States)

    Aguillo, Isidro F.

    2012-01-01

    The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

  3. Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

    Science.gov (United States)

    Stoenescu, Tudor M.; Woo, Simon S.

    2009-01-01

    In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

  4. World Reference Base for Soil Resources

    NARCIS (Netherlands)

    Deckers, J.A.; Driessen, P.M.; Nachtergaele, F.O.; Spaargaren, O.C.

    2002-01-01

    In 1998, the International Union of Soil Sciences (IUSS) officially adopted the world reference base for soil resources (WRB) as the Union's system for soil correlation. The structure, concepts, and definitions of the WRB are strongly influenced by the FAO-UNESCO legend of the soil map of the world

  5. Participation in community based natural resource management ...

    African Journals Online (AJOL)

    The study was on participation in Community Based Natural Resource Management Programme (CBNRMP) and its socio-economic effect on rural families in Ikwerre Area, Rivers State Nigeria. A structured questionnaire was administered to 60 beneficiaries of the programme. Data collected were subjected to descriptive ...

  6. SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

    Science.gov (United States)

    Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

    2017-01-01

    This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

  7. University Rankings and Social Science

    OpenAIRE

    Marginson, S.

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

  8. Dual channel rank-based intensity weighting for quantitative co-localization of microscopy images

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2011-10-21

    Abstract Background Accurate quantitative co-localization is a key parameter in the context of understanding the spatial co-ordination of molecules and therefore their function in cells. Existing co-localization algorithms consider either the presence of co-occurring pixels or correlations of intensity in regions of interest. Depending on the image source, and the algorithm selected, the co-localization coefficients determined can be highly variable, and often inaccurate. Furthermore, this choice of whether co-occurrence or correlation is the best approach for quantifying co-localization remains controversial. Results We have developed a novel algorithm to quantify co-localization that improves on and addresses the major shortcomings of existing co-localization measures. This algorithm uses a non-parametric ranking of pixel intensities in each channel, and the difference in ranks of co-localizing pixel positions in the two channels is used to weight the coefficient. This weighting is applied to co-occurring pixels thereby efficiently combining both co-occurrence and correlation. Tests with synthetic data sets show that the algorithm is sensitive to both co-occurrence and correlation at varying levels of intensity. Analysis of biological data sets demonstrate that this new algorithm offers high sensitivity, and that it is capable of detecting subtle changes in co-localization, exemplified by studies on a well characterized cargo protein that moves through the secretory pathway of cells. Conclusions This algorithm provides a novel way to efficiently combine co-occurrence and correlation components in biological images, thereby generating an accurate measure of co-localization. This approach of rank weighting of intensities also eliminates the need for manual thresholding of the image, which is often a cause of error in co-localization quantification. We envisage that this tool will facilitate the quantitative analysis of a wide range of biological data sets

  9. A least square support vector machine-based approach for contingency classification and ranking in a large power system

    Directory of Open Access Journals (Sweden)

    Bhanu Pratap Soni

    2016-12-01

    Full Text Available This paper proposes an effective supervised learning approach for static security assessment of a large power system. Supervised learning approach employs least square support vector machine (LS-SVM to rank the contingencies and predict the system severity level. The severity of the contingency is measured by two scalar performance indices (PIs: line MVA performance index (PIMVA and Voltage-reactive power performance index (PIVQ. SVM works in two steps. Step I is the estimation of both standard indices (PIMVA and PIVQ that is carried out under different operating scenarios and Step II contingency ranking is carried out based on the values of PIs. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus (New England system. The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center.

  10. Reliability-based decision making for selection of ready-mix concrete supply using stochastic superiority and inferiority ranking method

    International Nuclear Information System (INIS)

    Chou, Jui-Sheng; Ongkowijoyo, Citra Satria

    2015-01-01

    Corporate competitiveness is heavily influenced by the information acquired, processed, utilized and transferred by professional staff involved in the supply chain. This paper develops a decision aid for selecting on-site ready-mix concrete (RMC) unloading type in decision making situations involving multiple stakeholders and evaluation criteria. The uncertainty of criteria weights set by expert judgment can be transformed in random ways based on the probabilistic virtual-scale method within a prioritization matrix. The ranking is performed by grey relational grade systems considering stochastic criteria weight based on individual preference. Application of the decision aiding model in actual RMC case confirms that the method provides a robust and effective tool for facilitating decision making under uncertainty. - Highlights: • This study models decision aiding method to assess ready-mix concrete unloading type. • Applying Monte Carlo simulation to virtual-scale method achieves a reliable process. • Individual preference ranking method enhances the quality of global decision making. • Robust stochastic superiority and inferiority ranking obtains reasonable results

  11. Hierarchical partial order ranking

    International Nuclear Information System (INIS)

    Carlsen, Lars

    2008-01-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

  12. An Efficient Normalized Rank Based SVM for Room Level Indoor WiFi Localization with Diverse Devices

    Directory of Open Access Journals (Sweden)

    Yasmine Rezgui

    2017-01-01

    Full Text Available This paper proposes an efficient and effective WiFi fingerprinting-based indoor localization algorithm, which uses the Received Signal Strength Indicator (RSSI of WiFi signals. In practical harsh indoor environments, RSSI variation and hardware variance can significantly degrade the performance of fingerprinting-based localization methods. To address the problem of hardware variance and signal fluctuation in WiFi fingerprinting-based localization, we propose a novel normalized rank based Support Vector Machine classifier (NR-SVM. Moving from RSSI value based analysis to the normalized rank transformation based analysis, the principal features are prioritized and the dimensionalities of signature vectors are taken into account. The proposed method has been tested using sixteen different devices in a shopping mall with 88 shops. The experimental results demonstrate its robustness with no less than 98.75% correct estimation in 93.75% of the tested cases and 100% correct rate in 56.25% of cases. In the experiments, the new method shows better performance over the KNN, Naïve Bayes, Random Forest, and Neural Network algorithms. Furthermore, we have compared the proposed approach with three popular calibration-free transformation based methods, including difference method (DIFF, Signal Strength Difference (SSD, and the Hyperbolic Location Fingerprinting (HLF based SVM. The results show that the NR-SVM outperforms these popular methods.

  13. A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

    Directory of Open Access Journals (Sweden)

    Jiuqi Han

    2018-04-01

    Full Text Available Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods.

  14. Validation of a model for ranking aquaculture facilities for risk-based disease surveillance.

    Science.gov (United States)

    Diserens, Nicolas; Falzon, Laura Cristina; von Siebenthal, Beat; Schüpbach-Regula, Gertraud; Wahli, Thomas

    2017-09-15

    A semi-quantitative model for risk ranking of aquaculture facilities in Switzerland with regard to the introduction and spread of Viral Haemorrhagic Septicaemia (VHS) and Infectious Haematopoietic Necrosis (IHN) was developed in a previous study (Diserens et al., 2013). The objective of the present study was to validate this model using data collected during field visits on aquaculture sites in four Swiss cantons compared to data collected through a questionnaire in the previous study. A discrepancy between the values obtained with the two different methods was found in 32.8% of the parameters, resulting in a significant difference (pranking of Swiss aquaculture facilities according to their risk of getting infected with or spreading of VHS and IHN, as the five facilities that tested positive for these diseases in the last ten years were ranked as medium or high risk. Moreover, because the seven fish farms that were infected with Infectious Pancreatic Necrosis (IPN) during the same period also belonged to the risk categories medium and high, the classification appeared to correlate with the occurrence of this third viral fish disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Tackling Information Asymmetry in Networks: A New Entropy-Based Ranking Index

    Science.gov (United States)

    Barucca, Paolo; Caldarelli, Guido; Squartini, Tiziano

    2018-06-01

    Information is a valuable asset in socio-economic systems, a significant part of which is entailed into the network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant, systemic properties (e.g. the risk of contagion in a network of liabilities), agents capable of providing a better estimation of (otherwise) inaccessible network properties, ultimately have a competitive advantage. In this paper, we address the issue of quantifying the information asymmetry of nodes: to this aim, we define a novel index—InfoRank—intended to rank nodes according to their information content. In order to do so, each node ego-network is enforced as a constraint of an entropy-maximization problem and the subsequent uncertainty reduction is used to quantify the node-specific accessible information. We, then, test the performance of our ranking procedure in terms of reconstruction accuracy and show that it outperforms other centrality measures in identifying the "most informative" nodes. Finally, we discuss the socio-economic implications of network information asymmetry.

  16. A Topology Evolution Model Based on Revised PageRank Algorithm and Node Importance for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaogang Qi

    2015-01-01

    Full Text Available Wireless sensor network (WSN is a classical self-organizing communication network, and its topology evolution currently becomes one of the attractive issues in this research field. Accordingly, the problem is divided into two subproblems: one is to design a new preferential attachment method and the other is to analyze the dynamics of the network topology evolution. To solve the first subproblem, a revised PageRank algorithm, called Con-rank, is proposed to evaluate the node importance upon the existing node contraction, and then a novel preferential attachment is designed based on the node importance calculated by the proposed Con-rank algorithm. To solve the second one, we firstly analyze the network topology evolution dynamics in a theoretical way and then simulate the evolution process. Theoretical analysis proves that the network topology evolution of our model agrees with power-law distribution, and simulation results are well consistent with our conclusions obtained from the theoretical analysis and simultaneously show that our topology evolution model is superior to the classic BA model in the average path length and the clustering coefficient, and the network topology is more robust and can tolerate the random attacks.

  17. A rank-based algorithm of differential expression analysis for small cell line data with statistical control.

    Science.gov (United States)

    Li, Xiangyu; Cai, Hao; Wang, Xianlong; Ao, Lu; Guo, You; He, Jun; Gu, Yunyan; Qi, Lishuang; Guan, Qingzhou; Lin, Xu; Guo, Zheng

    2017-10-13

    To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data. © The Author 2017. Published by Oxford University Press.

  18. Using a consensus approach based on the conservation of inter-residue contacts to rank CAPRI models

    KAUST Repository

    Vangone, Anna

    2013-10-17

    Herein we propose the use of a consensus approach, CONSRANK, for ranking CAPRI models. CONSRANK relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. Models are ranked according to their ability to match the most frequently observed contacts. We applied CONSRANK to 19 CAPRI protein-protein targets, covering a wide range of prediction difficulty and involved in a variety of biological functions. CONSRANK results are consistently good, both in terms of native-like (NL) solutions ranked in the top positions and of values of the Area Under the receiver operating characteristic Curve (AUC). For targets having a percentage of NL solutions above 3%, an excellent performance is found, with AUC values approaching 1. For the difficult target T46, having only 3.4% NL solutions, the number of NL solutions in the top 5 and 10 ranked positions is enriched by a factor 30, and the AUC value is as high as 0.997. AUC values below 0.8 are only found for targets featuring a percentage of NL solutions within 1.1%. Remarkably, a false consensus emerges only in one case, T42, which happens to be an artificial protein, whose assembly details remain uncertain, based on controversial experimental data. We also show that CONSRANK still performs very well on a limited number of models, provided that more than 1 NL solution is included in the ensemble, thus extending its applicability to cases where few dozens of models are available.© 2013 Wiley Periodicals, Inc.

  19. Strategic Coupling Based on Natural Resources

    DEFF Research Database (Denmark)

    Hauge, Mads Martinus

    The topic of this thesis is the resourced-based industrialization of the Mekong River Delta (MRD) Region of Vietnam. It shows how a region is linked with the world market and how settlements and living conditions are being transformed as part of a globalized regional development. A modular theory......-building approach rooted in the Global Production Network (GPN) framework constitutes the analytical approach to the thesis, providing pertinent conceptualizations to explore and discuss how a globalized regional development unfolds. The main theoretical concept of the thesis is that of strategic coupling......, an established concept within the GPN framework that explores and explains how local assets are molded to complement the needs of the global market. However, existing applications of the notion of strategic coupling do not cover the situation in which a resource-based economy is coupled with the world market...

  20. PRIMAL: Page Rank-Based Indoor Mapping and Localization Using Gene-Sequenced Unlabeled WLAN Received Signal Strength

    Directory of Open Access Journals (Sweden)

    Mu Zhou

    2015-09-01

    Full Text Available Due to the wide deployment of wireless local area networks (WLAN, received signal strength (RSS-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM. Specifically, first of all, based on the observation of the motion patterns of the people in the target environment, we use the Allen logic to construct the mobility graph to characterize the connectivity among different areas of interest. Second, the concept of gene sequencing is utilized to assemble the sporadically-collected RSS sequences into a signal graph based on the transition relations among different RSS sequences. Third, we apply the graph drawing approach to exhibit both the mobility graph and signal graph in a more readable manner. Finally, the page rank (PR algorithm is proposed to construct the mapping from the signal graph into the mobility graph. The experimental results show that the proposed approach achieves satisfactory localization accuracy and meanwhile avoids the intensive time and labor cost involved in the conventional location fingerprinting-based indoor WLAN localization.

  1. PRIMAL: Page Rank-Based Indoor Mapping and Localization Using Gene-Sequenced Unlabeled WLAN Received Signal Strength.

    Science.gov (United States)

    Zhou, Mu; Zhang, Qiao; Xu, Kunjie; Tian, Zengshan; Wang, Yanmeng; He, Wei

    2015-09-25

    Due to the wide deployment of wireless local area networks (WLAN), received signal strength (RSS)-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL) by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM). Specifically, first of all, based on the observation of the motion patterns of the people in the target environment, we use the Allen logic to construct the mobility graph to characterize the connectivity among different areas of interest. Second, the concept of gene sequencing is utilized to assemble the sporadically-collected RSS sequences into a signal graph based on the transition relations among different RSS sequences. Third, we apply the graph drawing approach to exhibit both the mobility graph and signal graph in a more readable manner. Finally, the page rank (PR) algorithm is proposed to construct the mapping from the signal graph into the mobility graph. The experimental results show that the proposed approach achieves satisfactory localization accuracy and meanwhile avoids the intensive time and labor cost involved in the conventional location fingerprinting-based indoor WLAN localization.

  2. GIDEON: a comprehensive Web-based resource for geographic medicine

    Directory of Open Access Journals (Sweden)

    Berger Stephen A

    2005-04-01

    Full Text Available Abstract GIDEON (Global Infectious Diseases and Epidemiology Network is a web-based computer program designed for decision support and informatics in the field of Geographic Medicine. The first of four interactive modules generates a ranked differential diagnosis based on patient signs, symptoms, exposure history and country of disease acquisition. Additional options include syndromic disease surveillance capability and simulation of bioterrorism scenarios. The second module accesses detailed and current information regarding the status of 338 individual diseases in each of 220 countries. Over 50,000 disease images, maps and user-designed graphs may be downloaded for use in teaching and preparation of written materials. The third module is a comprehensive source on the use of 328 anti-infective drugs and vaccines, including a listing of over 9,500 international trade names. The fourth module can be used to characterize or identify any bacterium or yeast, based on laboratory phenotype. GIDEON is an up-to-date and comprehensive resource for Geographic Medicine.

  3. Rank-based testing of equal survivorship based on cross-sectional survival data with or without prospective follow-up.

    Science.gov (United States)

    Chan, Kwun Chuen Gary; Qin, Jing

    2015-10-01

    Existing linear rank statistics cannot be applied to cross-sectional survival data without follow-up since all subjects are essentially censored. However, partial survival information are available from backward recurrence times and are frequently collected from health surveys without prospective follow-up. Under length-biased sampling, a class of linear rank statistics is proposed based only on backward recurrence times without any prospective follow-up. When follow-up data are available, the proposed rank statistic and a conventional rank statistic that utilizes follow-up information from the same sample are shown to be asymptotically independent. We discuss four ways to combine these two statistics when follow-up is present. Simulations show that all combined statistics have substantially improved power compared with conventional rank statistics, and a Mantel-Haenszel test performed the best among the proposal statistics. The method is applied to a cross-sectional health survey without follow-up and a study of Alzheimer's disease with prospective follow-up. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  4. Using a consensus approach based on the conservation of inter-residue contacts to rank CAPRI models

    KAUST Repository

    Vangone, Anna; Cavallo, Luigi; Oliva, Romina M.

    2013-01-01

    Herein we propose the use of a consensus approach, CONSRANK, for ranking CAPRI models. CONSRANK relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. Models are ranked according to their ability to match the most

  5. Personalized PageRank Clustering: A graph clustering algorithm based on random walks

    Science.gov (United States)

    A. Tabrizi, Shayan; Shakery, Azadeh; Asadpour, Masoud; Abbasi, Maziar; Tavallaie, Mohammad Ali

    2013-11-01

    Graph clustering has been an essential part in many methods and thus its accuracy has a significant effect on many applications. In addition, exponential growth of real-world graphs such as social networks, biological networks and electrical circuits demands clustering algorithms with nearly-linear time and space complexity. In this paper we propose Personalized PageRank Clustering (PPC) that employs the inherent cluster exploratory property of random walks to reveal the clusters of a given graph. We combine random walks and modularity to precisely and efficiently reveal the clusters of a graph. PPC is a top-down algorithm so it can reveal inherent clusters of a graph more accurately than other nearly-linear approaches that are mainly bottom-up. It also gives a hierarchy of clusters that is useful in many applications. PPC has a linear time and space complexity and has been superior to most of the available clustering algorithms on many datasets. Furthermore, its top-down approach makes it a flexible solution for clustering problems with different requirements.

  6. Compression and Combining Based on Channel Shortening and Rank Reduction Technique for Cooperative Wireless Sensor Networks

    KAUST Repository

    Ahmed, Qasim Zeeshan

    2013-12-18

    This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of L sensors. As the destination has the capacity of processing only U out of these L signals, the strongest U signals are selected while the remaining (L?U) signals are suppressed. A preprocessing block similar to channel-shortening is proposed in this contribution. However, this preprocessing block employs a rank-reduction technique instead of channel-shortening. By employing this preprocessing, we are able to decrease the computational complexity of the system without affecting the bit error rate (BER) performance. From our simulations, it can be shown that these schemes outperform the channel-shortening schemes in terms of computational complexity. In addition, the proposed schemes have a superior BER performance as compared to channel-shortening schemes when sensors employ fixed gain amplification. However, for sensors which employ variable gain amplification, a tradeoff exists in terms of BER performance between the channel-shortening and these schemes. These schemes outperform channel-shortening scheme for lower signal-to-noise ratio.

  7. Reservoir characterization based on tracer response and rank analysis of production and injection rates

    Energy Technology Data Exchange (ETDEWEB)

    Refunjol, B.T. [Lagoven, S.A., Pdvsa (Venezuela); Lake, L.W. [Univ. of Texas, Austin, TX (United States)

    1997-08-01

    Quantification of the spatial distribution of properties is important for many reservoir-engineering applications. But, before applying any reservoir-characterization technique, the type of problem to be tackled and the information available should be analyzed. This is important because difficulties arise in reservoirs where production records are the only information for analysis. This paper presents the results of a practical technique to determine preferential flow trends in a reservoir. The technique is a combination of reservoir geology, tracer data, and Spearman rank correlation coefficient analysis. The Spearman analysis, in particular, will prove to be important because it appears to be insightful and uses injection/production data that are prevalent in circumstances where other data are nonexistent. The technique is applied to the North Buck Draw field, Campbell County, Wyoming. This work provides guidelines to assess information about reservoir continuity in interwell regions from widely available measurements of production and injection rates at existing wells. The information gained from the application of this technique can contribute to both the daily reservoir management and the future design, control, and interpretation of subsequent projects in the reservoir, without the need for additional data.

  8. Neophilia Ranking of Scientific Journals.

    Science.gov (United States)

    Packalen, Mikko; Bhattacharya, Jay

    2017-01-01

    The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

  9. Using Bibliographic Knowledge for Ranking in Scientific Publication Databases

    CERN Document Server

    Vesely, Martin; Le Meur, Jean-Yves

    2008-01-01

    Document ranking for scientific publications involves a variety of specialized resources (e.g. author or citation indexes) that are usually difficult to use within standard general purpose search engines that usually operate on large-scale heterogeneous document collections for which the required specialized resources are not always available for all the documents present in the collections. Integrating such resources into specialized information retrieval engines is therefore important to cope with community-specific user expectations that strongly influence the perception of relevance within the considered community. In this perspective, this paper extends the notion of ranking with various methods exploiting different types of bibliographic knowledge that represent a crucial resource for measuring the relevance of scientific publications. In our work, we experimentally evaluated the adequacy of two such ranking methods (one based on freshness, i.e. the publication date, and the other on a novel index, the ...

  10. Feasibility study of component risk ranking for plant maintenance

    International Nuclear Information System (INIS)

    Ushijima, Koji; Yonebayashi, Kenji; Narumiya, Yoshiyuki; Sakata, Kaoru; Kumano, Tetsuji

    1999-01-01

    Nuclear power is the base load electricity source in Japan, and reduction of operation and maintenance cost maintaining or improving plant safety is one of the major issues. Recently, Risk Informed Management (RIM) is focused as a solution. In this paper, the outline regarding feasibility study of component risk ranking for plant maintenance for a typical Japanese PWR plant is described. A feasibility study of component risk raking for plant maintenance optimization is performed on check valves and motor-operated valves. Risk ranking is performed in two steps using probabilistic analysis (quantitative method) for risk ranking of components, and deterministic examination (qualitative method) for component review. In this study, plant components are ranked from the viewpoint of plant safety / reliability, and the applicability for maintenance is assessed. As a result, distribution of maintenance resources using risk ranking is considered effective. (author)

  11. Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

    Science.gov (United States)

    Westermaier, Yvonne; Ruiz-Carmona, Sergio; Theret, Isabelle; Perron-Sierra, Françoise; Poissonnet, Guillaume; Dacquet, Catherine; Boutin, Jean A; Ducrot, Pierre; Barril, Xavier

    2017-08-01

    The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

  12. A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

    Science.gov (United States)

    Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

    2017-07-01

    Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

  13. Ranking nodes in growing networks: When PageRank fails.

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-10

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  14. SRMDAP: SimRank and Density-Based Clustering Recommender Model for miRNA-Disease Association Prediction

    Directory of Open Access Journals (Sweden)

    Xiaoying Li

    2018-01-01

    Full Text Available Aberrant expression of microRNAs (miRNAs can be applied for the diagnosis, prognosis, and treatment of human diseases. Identifying the relationship between miRNA and human disease is important to further investigate the pathogenesis of human diseases. However, experimental identification of the associations between diseases and miRNAs is time-consuming and expensive. Computational methods are efficient approaches to determine the potential associations between diseases and miRNAs. This paper presents a new computational method based on the SimRank and density-based clustering recommender model for miRNA-disease associations prediction (SRMDAP. The AUC of 0.8838 based on leave-one-out cross-validation and case studies suggested the excellent performance of the SRMDAP in predicting miRNA-disease associations. SRMDAP could also predict diseases without any related miRNAs and miRNAs without any related diseases.

  15. A Resource Based Framework for Planning and Replanning

    NARCIS (Netherlands)

    Van der Krogt, R.P.J.; De Weerdt, M.M.; Witteveen, C.

    2003-01-01

    We discuss a rigorous unifying framework for both planning and replanning, extending an existing logic-based approach to resource-based planning. The primitive concepts in this Action Resource Framework (ARF) are actions and resources. Actions consume and produce resources. Plans are structures

  16. Groundwater contaminant plume ranking

    International Nuclear Information System (INIS)

    1988-08-01

    Containment plumes at Uranium Mill Tailings Remedial Action (UMTRA) Project sites were ranked to assist in Subpart B (i.e., restoration requirements of 40 CFR Part 192) compliance strategies for each site, to prioritize aquifer restoration, and to budget future requests and allocations. The rankings roughly estimate hazards to the environment and human health, and thus assist in determining for which sites cleanup, if appropriate, will provide the greatest benefits for funds available. The rankings are based on the scores that were obtained using the US Department of Energy's (DOE) Modified Hazard Ranking System (MHRS). The MHRS and HRS consider and score three hazard modes for a site: migration, fire and explosion, and direct contact. The migration hazard mode score reflects the potential for harm to humans or the environment from migration of a hazardous substance off a site by groundwater, surface water, and air; it is a composite of separate scores for each of these routes. For ranking the containment plumes at UMTRA Project sites, it was assumed that each site had been remediated in compliance with the EPA standards and that relict contaminant plumes were present. Therefore, only the groundwater route was scored, and the surface water and air routes were not considered. Section 2.0 of this document describes the assumptions and procedures used to score the groundwater route, and Section 3.0 provides the resulting scores for each site. 40 tabs

  17. Resource allocation based on cost efficiency

    DEFF Research Database (Denmark)

    Dehnokhalaji, Akram; Ghiyasi, Mojtaba; Korhonen, Pekka

    2017-01-01

    -objective linear programming problem using two different strategies. First, we propose an RA model which keeps the cost efficiencies of units unchanged. This is done assuming fixed technical and allocative efficiencies. The approach is based on the assumption that the decision maker (DM) may not have big changes......In this paper, we consider a resource allocation (RA) problem and develop an approach based on cost (overall) efficiency. The aim is to allocate some inputs among decision making units (DMUs) in such way that their cost efficiencies improve or stay unchanged after RA. We formulate a multi...... in the structure of DMUs within a short term. The second strategy does not impose any restrictions on technical and allocative efficiencies. It guarantees that none of the cost efficiencies of DMUs get worse after RA, and the improvement for units is possible if it is feasible and beneficial. Two numerical...

  18. Quantitative Analysis of Mixtures of Monoprotic Acids Applying Modified Model-Based Rank Annihilation Factor Analysis on Variation Matrices of Spectrophotometric Acid-Base Titrations

    Directory of Open Access Journals (Sweden)

    Ebrahim Ghorbani-Kalhor

    2015-04-01

    Full Text Available In the current work, a new version of rank annihilation factor analysis was developedto circumvent the rank deficiency problem in multivariate data measurements.Simultaneous determination of dissociation constant and concentration of monoprotic acids was performed by applying model-based rank annihilation factor analysis on variation matrices of spectrophotometric acid-base titrations data. Variation matrices can be obtained by subtracting first row of data matrix from all rows of the main data matrix. This method uses variation matrices instead of multivariate spectrophotometric acid-base titrations matrices to circumvent the rank deficiency problem in the rank quantitation step. The applicability of this approach was evaluated by simulated data at first stage, then the binary mixtures of ascorbic and sorbic acids as model compounds were investigated by the proposed method. At the end, the proposed method was successfully applied for resolving the ascorbic and sorbic acid in an orange juice real sample. Therefore, unique results were achieved by applying rank annihilation factor analysis on variation matrix and using hard soft model combination advantage without any problem and difficulty in rank determination. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-bidi-language:AR-SA;}    

  19. Ranking economic history journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    2010-01-01

    This study ranks-for the first time-12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We also...... compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential for economic...... history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

  20. Ranking Economic History Journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    This study ranks - for the first time - 12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We...... also compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential...... for economic history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

  1. Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction

    Science.gov (United States)

    Fang, Shiting; Wang, Huafeng; Liu, Yueliang; Zhang, Minghui; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

    2017-10-01

    Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al’s algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al’s method, thus indicating the effectivity and competitiveness of the proposed algorithm.

  2. 14 CFR 1214.1105 - Final ranking.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

  3. The effect of resource based view on sustainable capability advantage

    Directory of Open Access Journals (Sweden)

    Mostafa Jafari

    2014-12-01

    Full Text Available Nowadays, it is important to achieve and to sustain an organization’s competitive advantage in complex environments. This paper evaluates different concepts that have led to such benefits. The study sheds light on resource based view (RBV and its role to reach sustainable competitive advantage (SCA within banking industry of Iran. A valid research instrument was utilized to conduct a survey of 150 top- and middle-level managers from Mellat bank of Iran. With a response rate of 81.3 percent, 122 questionnaires were returned while a number of valid and usable questionnaires were 101. In order to determine validity of questionnaire, the content validity and Cronbach's alpha were used to determine the reliability of the questionnaire (RBV questionnaire 0.934, SCA questionnaire 0.843. The study utilized structural equation modelling, and a series of exploratory and confirmatory factor analyses and they tested the integrated model of MKM and SCA. Statistical support was found for the hypothesized relationships. Moreover it has been shown that RBV had the greatest effect on the market centered SCA, while it had the least influence on the financial centered. The findings offer valuable insights on the generalizability of MKM in a research setting. Structural equation modeling has been implemented and the study also used freedman test to rank the factors and the results show that communication was the most important factor (4.41, followed by process (4.03, knowledge implementation (2.79, decision making (2.54 and human resources (1.22 was the last important factor.

  4. Preliminary research on quantitative methods of water resources carrying capacity based on water resources balance sheet

    Science.gov (United States)

    Wang, Yanqiu; Huang, Xiaorong; Gao, Linyun; Guo, Biying; Ma, Kai

    2018-06-01

    Water resources are not only basic natural resources, but also strategic economic resources and ecological control factors. Water resources carrying capacity constrains the sustainable development of regional economy and society. Studies of water resources carrying capacity can provide helpful information about how the socioeconomic system is both supported and restrained by the water resources system. Based on the research of different scholars, major problems in the study of water resources carrying capacity were summarized as follows: the definition of water resources carrying capacity is not yet unified; the methods of carrying capacity quantification based on the definition of inconsistency are poor in operability; the current quantitative research methods of water resources carrying capacity did not fully reflect the principles of sustainable development; it is difficult to quantify the relationship among the water resources, economic society and ecological environment. Therefore, it is necessary to develop a better quantitative evaluation method to determine the regional water resources carrying capacity. This paper proposes a new approach to quantifying water resources carrying capacity (that is, through the compilation of the water resources balance sheet) to get a grasp of the regional water resources depletion and water environmental degradation (as well as regional water resources stock assets and liabilities), figure out the squeeze of socioeconomic activities on the environment, and discuss the quantitative calculation methods and technical route of water resources carrying capacity which are able to embody the substance of sustainable development.

  5. Freudenthal ranks: GHZ versus W

    International Nuclear Information System (INIS)

    Borsten, L

    2013-01-01

    The Hilbert space of three-qubit pure states may be identified with a Freudenthal triple system. Every state has an unique Freudenthal rank ranging from 1 to 4, which is determined by a set of automorphism group covariants. It is shown here that the optimal success rates for winning a three-player non-local game, varying over all local strategies, are strictly ordered by the Freudenthal rank of the shared three-qubit resource. (paper)

  6. Ranking procedure based on mechanical, durability and thermal behavior of mortars with incorporation of phase change materials

    Directory of Open Access Journals (Sweden)

    Cunha, S.

    2015-12-01

    Full Text Available Nowadays, considering the high variety of construction products, adequate material selection, based on their properties and function, becomes increasingly important. In this research, a ranking procedure developed by Czarnecki and Lukowski is applied in mortars with incorporation of phase change materials (PCM. The ranking procedure transforms experimental results of properties into one numerical value. The products can be classified according to their individual properties or even an optimized combination of different properties. The main purpose of this study was the ranking of mortars with incorporation of different contents of PCM based in different binders. Aerial lime, hydraulic lime, gypsum and cement were the binders studied. For each binder, three different mortars were developed. Reference mortars, mortars with incorporation of 40% of PCM and mortars with incorporation of 40% of PCM and 1% of fibers, were tested. Results show that the incorporation of PCM in mortars changes their global performance.Actualmente, existen varios productos de construcción, siendo importante una adecuada selección, con base en sus principales propiedades y funciones. En esta investigación se aplicó un procedimiento de clasificación desarrollado por Czarnecki y Lukowski, en morteros con incorporación de materiales de cambio de fase (PCM. Este procedimiento transforma los resultados experimentales de las propiedades en un único valor numérico. Los productos se clasifican de acuerdo con sus propiedades individuales o en una combinación optimizada de diferentes propiedades. El principal objetivo de este estudio fue la clasificación de morteros basado en los diferentes aglutinantes con incorporación de diferentes cantidades de PCM. Los aglutinantes utilizados fueran la cal aérea, cal hidráulica, yeso y cemento. Para cada aglutinante se han desarrollado tres morteros, siendo morteros de referencia, con incorporación de 40% de PCM y con incorporaci

  7. Ranking coastal flood protection designs from engineered to nature-based

    NARCIS (Netherlands)

    Nat, van der A.; Vellinga, P.; Leemans, R.; Slobbe, van E.

    2016-01-01

    Compared to traditional hard engineering, nature-based flood protection can be more cost effective, use up less raw materials, increase system adaptability and present opportunities to improve ecosystem functioning. However, high flood safety standards cause the need to combine nature-based

  8. In Silico target fishing: addressing a "Big Data" problem by ligand-based similarity rankings with data fusion.

    Science.gov (United States)

    Liu, Xian; Xu, Yuan; Li, Shanshan; Wang, Yulan; Peng, Jianlong; Luo, Cheng; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

    2014-01-01

    Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery.

  9. Opening Up Natural Resource Based Industries for Innovation (LAC ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Opening Up Natural Resource Based Industries for Innovation (LAC). Commodities based on natural resources account for at least half of the exports of two-thirds of the countries in Latin America and the Caribbean (LAC). There is growing concern, however, that existing natural resource-based industries are ...

  10. Ranking Specific Sets of Objects.

    Science.gov (United States)

    Maly, Jan; Woltran, Stefan

    2017-01-01

    Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

  11. Resource Based Multi Agent Plan Merging : Framework and application

    NARCIS (Netherlands)

    De Weerdt, M.M.; Van der Krogt, R.P.J.; Witteveen, C.

    2003-01-01

    We discuss a resource-based planning framework where agents are able to merge plans by exchanging resources. In this framework, plans are specified as structured objects composed of resource consuming and resource producing processes (actions). A plan itself can also be conceived as a process

  12. Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach.

    Science.gov (United States)

    Richardson, Rodney T; Lin, Chia-Hua; Quijia, Juan O; Riusech, Natalia S; Goodell, Karen; Johnson, Reed M

    2015-11-01

    Difficulties inherent in microscopic pollen identification have resulted in limited implementation for large-scale studies. Metabarcoding, a relatively novel approach, could make pollen analysis less onerous; however, improved understanding of the quantitative capacity of various plant metabarcode regions and primer sets is needed to ensure that such applications are accurate and precise. We applied metabarcoding, targeting the ITS2, matK, and rbcL loci, to characterize six samples of pollen collected by honey bees, Apis mellifera. Additionally, samples were analyzed by light microscopy. We found significant rank-based associations between the relative abundance of pollen types within our samples as inferred by the two methods. Our findings suggest metabarcoding data from plastid loci, as opposed to the ribosomal locus, are more reliable for quantitative characterization of pollen assemblages. Furthermore, multilocus metabarcoding of pollen may be more reliable than single-locus analyses, underscoring the need for discovering novel barcodes and barcode combinations optimized for molecular palynology.

  13. A multicriteria model for ranking of improvement approaches in construction companies based on the PROMETHÉE II method

    Directory of Open Access Journals (Sweden)

    Renata Maciel de Melo

    2015-03-01

    Full Text Available The quality of the construction production process may be improved using several different methods such as Lean Construction, ISO 9001, ISO 14001 or ISO 18001. Construction companies need a preliminary study and systematic implementation of changes to become more competitive and efficient. This paper presents a multicriteria decision model for the selection and ranking of such alternatives for improvement approaches regarding the aspects of quality, sustainability and safety, based on the PROMETHEE II method. The adoption of this model provides more confidence and visibility for decision makers. One of the differentiators of this model is the use of a fragmented set of improvement alternatives. These alternatives were combined with some restrictions to create a global set of alternatives. An application to three scenarios, considering realistic data, was developed. The results of the application show that the model should be incorporated into the strategic planning process of organizations.

  14. Development and first application of an operating events ranking tool

    International Nuclear Information System (INIS)

    Šimić, Zdenko; Zerger, Benoit; Banov, Reni

    2015-01-01

    Highlights: • A method using analitycal hierarchy process for ranking operating events is developed and tested. • The method is applied for 5 years of U.S. NRC Licensee Event Reports (1453 events). • Uncertainty and sensitivity of the ranking results are evaluated. • Real events assessment shows potential of the method for operating experience feedback. - Abstract: The operating experience feedback is important for maintaining and improving safety and availability in nuclear power plants. Detailed investigation of all events is challenging since it requires excessive resources, especially in case of large event databases. This paper presents an event groups ranking method to complement the analysis of individual operating events. The basis for the method is the use of an internationally accepted events characterization scheme that allows different ways of events grouping and ranking. The ranking method itself consists of implementing the analytical hierarchy process (AHP) by means of a custom developed tool which allows events ranking based on ranking indexes pre-determined by expert judgment. Following the development phase, the tool was applied to analyze a complete set of 5 years of real nuclear power plants operating events (1453 events). The paper presents the potential of this ranking method to identify possible patterns throughout the event database and therefore to give additional insights into the events as well as to give quantitative input for the prioritization of further more detailed investigation of selected event groups

  15. Analysis of temporal-longitudinal-latitudinal characteristics in the global ionosphere based on tensor rank-1 decomposition

    Science.gov (United States)

    Lu, Shikun; Zhang, Hao; Li, Xihai; Li, Yihong; Niu, Chao; Yang, Xiaoyun; Liu, Daizhi

    2018-03-01

    Combining analyses of spatial and temporal characteristics of the ionosphere is of great significance for scientific research and engineering applications. Tensor decomposition is performed to explore the temporal-longitudinal-latitudinal characteristics in the ionosphere. Three-dimensional tensors are established based on the time series of ionospheric vertical total electron content maps obtained from the Centre for Orbit Determination in Europe. To obtain large-scale characteristics of the ionosphere, rank-1 decomposition is used to obtain U^{(1)}, U^{(2)}, and U^{(3)}, which are the resulting vectors for the time, longitude, and latitude modes, respectively. Our initial finding is that the correspondence between the frequency spectrum of U^{(1)} and solar variation indicates that rank-1 decomposition primarily describes large-scale temporal variations in the global ionosphere caused by the Sun. Furthermore, the time lags between the maxima of the ionospheric U^{(2)} and solar irradiation range from 1 to 3.7 h without seasonal dependence. The differences in time lags may indicate different interactions between processes in the magnetosphere-ionosphere-thermosphere system. Based on the dataset displayed in the geomagnetic coordinates, the position of the barycenter of U^{(3)} provides evidence for north-south asymmetry (NSA) in the large-scale ionospheric variations. The daily variation in such asymmetry indicates the influences of solar ionization. The diurnal geomagnetic coordinate variations in U^{(3)} show that the large-scale EIA (equatorial ionization anomaly) variations during the day and night have similar characteristics. Considering the influences of geomagnetic disturbance on ionospheric behavior, we select the geomagnetic quiet GIMs to construct the ionospheric tensor. The results indicate that the geomagnetic disturbances have little effect on large-scale ionospheric characteristics.

  16. A Survey on PageRank Computing

    OpenAIRE

    Berkhin, Pavel

    2005-01-01

    This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

  17. Knowledge based ranking algorithm for comparative assessment of post-closure care needs of closed landfills

    International Nuclear Information System (INIS)

    Sizirici, Banu; Tansel, Berrin; Kumar, Vivek

    2011-01-01

    Post-closure care (PCC) activities at landfills include cap maintenance; water quality monitoring; maintenance and monitoring of the gas collection/control system, leachate collection system, groundwater monitoring wells, and surface water management system; and general site maintenance. The objective of this study was to develop an integrated data and knowledge based decision making tool for preliminary estimation of PCC needs at closed landfills. To develop the decision making tool, 11 categories of parameters were identified as critical areas which could affect future PCC needs. Each category was further analyzed by detailed questions which could be answered with limited data and knowledge about the site, its history, location, and site specific characteristics. Depending on the existing knowledge base, a score was assigned to each question (on a scale 1-10, as 1 being the best and 10 being the worst). Each category was also assigned a weight based on its relative importance on the site conditions and PCC needs. The overall landfill score was obtained from the total weighted sum attained. Based on the overall score, landfill conditions could be categorized as critical, acceptable, or good. Critical condition indicates that the landfill may be a threat to the human health and the environment and necessary steps should be taken. Acceptable condition indicates that the landfill is currently stable and the monitoring should be continued. Good condition indicates that the landfill is stable and the monitoring activities can be reduced in the future. The knowledge base algorithm was applied to two case study landfills for preliminary assessment of PCC performance.

  18. Knowledge based ranking algorithm for comparative assessment of post-closure care needs of closed landfills.

    Science.gov (United States)

    Sizirici, Banu; Tansel, Berrin; Kumar, Vivek

    2011-06-01

    Post-closure care (PCC) activities at landfills include cap maintenance; water quality monitoring; maintenance and monitoring of the gas collection/control system, leachate collection system, groundwater monitoring wells, and surface water management system; and general site maintenance. The objective of this study was to develop an integrated data and knowledge based decision making tool for preliminary estimation of PCC needs at closed landfills. To develop the decision making tool, 11 categories of parameters were identified as critical areas which could affect future PCC needs. Each category was further analyzed by detailed questions which could be answered with limited data and knowledge about the site, its history, location, and site specific characteristics. Depending on the existing knowledge base, a score was assigned to each question (on a scale 1-10, as 1 being the best and 10 being the worst). Each category was also assigned a weight based on its relative importance on the site conditions and PCC needs. The overall landfill score was obtained from the total weighted sum attained. Based on the overall score, landfill conditions could be categorized as critical, acceptable, or good. Critical condition indicates that the landfill may be a threat to the human health and the environment and necessary steps should be taken. Acceptable condition indicates that the landfill is currently stable and the monitoring should be continued. Good condition indicates that the landfill is stable and the monitoring activities can be reduced in the future. The knowledge base algorithm was applied to two case study landfills for preliminary assessment of PCC performance. Copyright © 2011 Elsevier Ltd. All rights reserved.

  19. Optimizing Search and Ranking in Folksonomy Systems by Exploiting Context Information

    Science.gov (United States)

    Abel, Fabian; Henze, Nicola; Krause, Daniel

    Tagging systems enable users to annotate resources with freely chosen keywords. The evolving bunch of tag assignments is called folksonomy and there exist already some approaches that exploit folksonomies to improve resource retrieval. In this paper, we analyze and compare graph-based ranking algorithms: FolkRank and SocialPageRank. We enhance these algorithms by exploiting the context of tags, and evaluate the results on the GroupMe! dataset. In GroupMe!, users can organize and maintain arbitrary Web resources in self-defined groups. When users annotate resources in GroupMe!, this can be interpreted in context of a certain group. The grouping activity itself is easy for users to perform. However, it delivers valuable semantic information about resources and their context. We present GRank that uses the context information to improve and optimize the detection of relevant search results, and compare different strategies for ranking result lists in folksonomy systems.

  20. [HUMAN RESOURCES MANAGEMENT BASED ON COMPETENCIES].

    Science.gov (United States)

    Larumbe Andueza, Ma Carmen; De Mendoza Cánton, Juana Hermoso

    2016-05-01

    We are living in a time with a lot of changes in which health organizations have more challenges to face. One of them is to recognize, strengthen, develop and retain the talent they have. Competency-based human resources management is emerging as a tool that contributes to achieve that aim. Competencies from the generic or characteristic perspective: personality traits, values and motivations, which are deeply rooted in the person. Through elaborating a competencies map for the organization, and identifying the job competencies profile, above all in key jobs, the employees know what it is going to expect from them. After, detect and cover the learning needs, it is possible to achieve better adjust between worker-job. The nursing unit manager is a key job because it is a link between management team and nursing team. The way that it is performed, it will have impact on the quality of care and its team motivation. So, the most adequate person who covers this job would have a part of knowledge, skills, attitudes and compatible interests with her job. Competency-based management helps identify both the potential and learning needs to performing this job.

  1. Ranking nodes in growing networks: When PageRank fails

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-01

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  2. Design and analysis of a ranking approach to private location-based services

    DEFF Research Database (Denmark)

    Yiu, Ma Lung; Jensen, Christian S.; Møller, Jesper

    2011-01-01

    solution that expresses the server-side functionality in a single SQL statement. In its basic form, SpaceTwist utilizes well-known incremental NN query processing on the server. When augmented with a server-side granular search technique, SpaceTwist is capable of exploiting relaxed query accuracy......Twist, aims to offer location privacy for k nearest neighbor (kNN) queries at low communication cost without requiring a trusted anonymizer. The solution can be used with a conventional DBMS as well as with a server optimized for location-based services. In particular, we believe that this is the first...

  3. Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes.

    Directory of Open Access Journals (Sweden)

    Christof Winter

    Full Text Available Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

  4. Application of fuzzy-MOORA method: Ranking of components for reliability estimation of component-based software systems

    Directory of Open Access Journals (Sweden)

    Zeeshan Ali Siddiqui

    2016-01-01

    Full Text Available Component-based software system (CBSS development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.

  5. Diversifying customer review rankings.

    Science.gov (United States)

    Krestel, Ralf; Dokoohaki, Nima

    2015-06-01

    E-commerce Web sites owe much of their popularity to consumer reviews accompanying product descriptions. On-line customers spend hours and hours going through heaps of textual reviews to decide which products to buy. At the same time, each popular product has thousands of user-generated reviews, making it impossible for a buyer to read everything. Current approaches to display reviews to users or recommend an individual review for a product are based on the recency or helpfulness of each review. In this paper, we present a framework to rank product reviews by optimizing the coverage of the ranking with respect to sentiment or aspects, or by summarizing all reviews with the top-K reviews in the ranking. To accomplish this, we make use of the assigned star rating for a product as an indicator for a review's sentiment polarity and compare bag-of-words (language model) with topic models (latent Dirichlet allocation) as a mean to represent aspects. Our evaluation on manually annotated review data from a commercial review Web site demonstrates the effectiveness of our approach, outperforming plain recency ranking by 30% and obtaining best results by combining language and topic model representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Identifying and ranking implicit leadership strategies to promote evidence-based practice implementation in addiction health services.

    Science.gov (United States)

    Guerrero, Erick G; Padwa, Howard; Fenwick, Karissa; Harris, Lesley M; Aarons, Gregory A

    2016-05-14

    Despite a solid research base supporting evidence-based practices (EBPs) for addiction treatment such as contingency management and medication-assisted treatment, these services are rarely implemented and delivered in community-based addiction treatment programs in the USA. As a result, many clients do not benefit from the most current and efficacious treatments, resulting in reduced quality of care and compromised treatment outcomes. Previous research indicates that addiction program leaders play a key role in supporting EBP adoption and use. The present study expanded on this previous work to identify strategies that addiction treatment program leaders report using to implement new practices. We relied on a staged and iterative mixed-methods approach to achieve the following four goals: (a) collect data using focus groups and semistructured interviews and conduct analyses to identify implicit managerial strategies for implementation, (b) use surveys to quantitatively rank strategy effectiveness, (c) determine how strategies fit with existing theories of organizational management and change, and (d) use a consensus group to corroborate and expand on the results of the previous three stages. Each goal corresponded to a methodological phase, which included data collection and analytic approaches to identify and evaluate leadership interventions that facilitate EBP implementation in community-based addiction treatment programs. Findings show that the top-ranked strategies involved the recruitment and selection of staff members receptive to change, offering support and requesting feedback during the implementation process, and offering in vivo and hands-on training. Most strategies corresponded to emergent implementation leadership approaches that also utilize principles of transformational and transactional leadership styles. Leadership behaviors represented orientations such as being proactive to respond to implementation needs, supportive to assist staff members

  7. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-11-19

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  8. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2012-01-01

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  9. Multiple graph regularized protein domain ranking.

    Science.gov (United States)

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2012-11-19

    Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  10. Multiple graph regularized protein domain ranking

    Directory of Open Access Journals (Sweden)

    Wang Jim

    2012-11-01

    Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  11. Risk-based ranking of dominant contributors to maritime pollution events

    International Nuclear Information System (INIS)

    Wheeler, T.A.

    1993-01-01

    This report describes a conceptual approach for identifying dominant contributors to risk from maritime shipping of hazardous materials. Maritime transportation accidents are relatively common occurrences compared to more frequently analyzed contributors to public risk. Yet research on maritime safety and pollution incidents has not been guided by a systematic, risk-based approach. Maritime shipping accidents can be analyzed using event trees to group the accidents into 'bins,' or groups, of similar characteristics such as type of cargo, location of accident (e.g., harbor, inland waterway), type of accident (e.g., fire, collision, grounding), and size of release. The importance of specific types of events to each accident bin can be quantified. Then the overall importance of accident events to risk can be estimated by weighting the events' individual bin importance measures by the risk associated with each accident bin. 4 refs., 3 figs., 6 tabs

  12. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

    2014-01-01

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

  13. Assessing the contribution of Community-Based Natural Resources ...

    African Journals Online (AJOL)

    Adisa, B.O.

    2013-09-20

    Sep 20, 2013 ... environmental sustainability in Ondo State, Nigeria. Adisa, Banji O. ... Key words: Assessment, community-based, natural resources, socio-environmental sustainability, ... Natural resources occur within environments that are.

  14. Ranking of tree-ring based temperature reconstructions of the past millennium

    Science.gov (United States)

    Esper, Jan; Krusic, Paul J.; Ljungqvist, Fredrik C.; Luterbacher, Jürg; Carrer, Marco; Cook, Ed; Davi, Nicole K.; Hartl-Meier, Claudia; Kirdyanov, Alexander; Konter, Oliver; Myglan, Vladimir; Timonen, Mauri; Treydte, Kerstin; Trouet, Valerie; Villalba, Ricardo; Yang, Bao; Büntgen, Ulf

    2016-08-01

    Tree-ring chronologies are widely used to reconstruct high-to low-frequency variations in growing season temperatures over centuries to millennia. The relevance of these timeseries in large-scale climate reconstructions is often determined by the strength of their correlation against instrumental temperature data. However, this single criterion ignores several important quantitative and qualitative characteristics of tree-ring chronologies. Those characteristics are (i) data homogeneity, (ii) sample replication, (iii) growth coherence, (iv) chronology development, and (v) climate signal including the correlation with instrumental data. Based on these 5 characteristics, a reconstruction-scoring scheme is proposed and applied to 39 published, millennial-length temperature reconstructions from Asia, Europe, North America, and the Southern Hemisphere. Results reveal no reconstruction scores highest in every category and each has their own strengths and weaknesses. Reconstructions that perform better overall include N-Scan and Finland from Europe, E-Canada from North America, Yamal and Dzhelo from Asia. Reconstructions performing less well include W-Himalaya and Karakorum from Asia, Tatra and S-Finland from Europe, and Great Basin from North America. By providing a comprehensive set of criteria to evaluate tree-ring chronologies we hope to improve the development of large-scale temperature reconstructions spanning the past millennium. All reconstructions and their corresponding scores are provided at http://www.blogs.uni-mainz.de/fb09climatology.

  15. Feasibility of developing risk-based rankings of pressure boundary systems for inservice inspection

    Energy Technology Data Exchange (ETDEWEB)

    Vo, T.V.; Smith, B.W.; Simonen, F.A.; Gore, B.F.

    1994-08-01

    The goals of the Evaluation and Improvement of Non-destructive Examination Reliability for the In-service Inspection of Light Water Reactors Program sponsored by the Nuclear Regulatory Commission at Pacific Northwest Laboratory (PNL) are to (1) assess current ISI techniques and requirements for all pressure boundary systems and components, (2) determine if improvements to the requirements are needed, and (3) if necessary, develop recommendations for revising the applicable ASME Codes and regulatory requirements. In evaluating approaches that could be used to provide a technical basis for improved inservice inspection plans, PNL has developed and applied a method that uses results of probabilistic risk assessment (PRA) to establish piping system ISI requirements. In the PNL program, the feasibility of generic ISI requirements is being addressed in two phases. Phase I involves identifying and prioritizing the systems most relevant to plant safety. The results of these evaluations will be later consolidated into requirements for comprehensive inservice inspection of nuclear power plant components that will be developed in Phase II. This report presents Phase I evaluations for eight selected plants and attempts to compare these PRA-based inspection priorities with current ASME Section XI requirements for Class 1, 2 and 3 systems. These results show that there are generic insights that can be extrapolated from the selected plants to specific classes of light water reactors.

  16. Feasibility of developing risk-based rankings of pressure boundary systems for inservice inspection

    International Nuclear Information System (INIS)

    Vo, T.V.; Smith, B.W.; Simonen, F.A.; Gore, B.F.

    1994-08-01

    The goals of the Evaluation and Improvement of Non-destructive Examination Reliability for the In-service Inspection of Light Water Reactors Program sponsored by the Nuclear Regulatory Commission at Pacific Northwest Laboratory (PNL) are to (1) assess current ISI techniques and requirements for all pressure boundary systems and components, (2) determine if improvements to the requirements are needed, and (3) if necessary, develop recommendations for revising the applicable ASME Codes and regulatory requirements. In evaluating approaches that could be used to provide a technical basis for improved inservice inspection plans, PNL has developed and applied a method that uses results of probabilistic risk assessment (PRA) to establish piping system ISI requirements. In the PNL program, the feasibility of generic ISI requirements is being addressed in two phases. Phase I involves identifying and prioritizing the systems most relevant to plant safety. The results of these evaluations will be later consolidated into requirements for comprehensive inservice inspection of nuclear power plant components that will be developed in Phase II. This report presents Phase I evaluations for eight selected plants and attempts to compare these PRA-based inspection priorities with current ASME Section XI requirements for Class 1, 2 and 3 systems. These results show that there are generic insights that can be extrapolated from the selected plants to specific classes of light water reactors

  17. Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

    Directory of Open Access Journals (Sweden)

    Jing Zhao

    Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

  18. U.S. Natural Gas Storage Risk-Based Ranking Methodology and Results

    Energy Technology Data Exchange (ETDEWEB)

    Folga, Steve [Argonne National Lab. (ANL), Argonne, IL (United States); Portante, Edgar [Argonne National Lab. (ANL), Argonne, IL (United States); Shamsuddin, Shabbir [Argonne National Lab. (ANL), Argonne, IL (United States); Tompkins, Angeli [Argonne National Lab. (ANL), Argonne, IL (United States); Talaber, Leah [Argonne National Lab. (ANL), Argonne, IL (United States); McLamore, Mike [Argonne National Lab. (ANL), Argonne, IL (United States); Kavicky, Jim [Argonne National Lab. (ANL), Argonne, IL (United States); Conzelmann, Guenter [Argonne National Lab. (ANL), Argonne, IL (United States); Levin, Todd [Argonne National Lab. (ANL), Argonne, IL (United States)

    2016-10-01

    This report summarizes the methodology and models developed to assess the risk to energy delivery from the potential loss of underground gas storage (UGS) facilities located within the United States. The U.S. has a total of 418 existing storage fields, of which 390 are currently active. The models estimate the impacts of a disruption of each of the active UGS facilities on their owners/operators, including (1) local distribution companies (LDCs), (2) directly connected transporting pipelines and thus on the customers in downstream States, and (3) third-party entities and thus on contracted customers expecting the gas shipment. Impacts are measured across all natural gas customer classes. For the electric sector, impacts are quantified in terms of natural gas-fired electric generation capacity potentially affected from the loss of a UGS facility. For the purpose of calculating the overall supply risk, the overall consequence of the disruption of an UGS facility across all customer classes is expressed in terms of the number of expected equivalent residential customer outages per year, which combines the unit business interruption cost per customer class and the estimated number of affected natural gas customers with estimated probabilities of UGS disruptions. All models and analyses are based on publicly available data. The report presents a set of findings and recommendations in terms of data, further analyses, regulatory requirements and standards, and needs to improve gas/electric industry coordination for electric reliability.

  19. Further assessment of scavenging feed resource base

    International Nuclear Information System (INIS)

    Sonaiya, E.B.; Dazogbo, J.S.; Olukosi, O.A.

    2002-01-01

    The scavenging feed resource base (SFRB) was estimated in four villages located in a rainforest ecozone in Nigeria. The average SFRB estimated for the villages was 110 kg dry weight/family flock/year. Productivity of the birds in the villages was low. A low survivability of chicks was detected indicating a lot of wastage of eggs that could have been used for human consumption. The SFRB was low in nutritive value with less than 2 g crude protein (CP) available to each bird daily. To more quantitatively describe the SFRB, the concept of using bird unit in determining what is available to each bird is suggested. This helped in evaluating at first glance the differential accessibility of each class of bird to the SFRB and assisted in strategic supplementation of the SFRB. The use of predictors of the SFRB could help in establishing prediction equation which would help in predicting the carrying capacity of the SFRB and in determining the optimum flock biomass more accurately. (author)

  20. Patient flow based allocation of hospital resources.

    Science.gov (United States)

    Vissers, J M

    1995-01-01

    The current practice of allocating resources within a hospital introduces peaks and troughs in the workloads of departments and leads therefore to loss of capacity. This happens when requirements for capacity coordination are not adequately taken into account in the decision making process of allocating resources to specialties. The first part of this research involved an analysis of the hospital's production system on dependencies between resources, resulting in a number of capacity coordination requirements that need to be fulfilled for optimized resource utilization. The second, modelling, part of the study involved the development of a framework for resource management decision making, of a set of computer models to support hospital managerial decision making on resource allocation issues in various parts of the hospital, and of an implementation strategy for the application of the models to concrete hospital settings. The third part of the study was devoted to a number of case-studies, illustrating the use of the models when applied in various resource management projects, such as a reorganization of an operating theatre timetable, or the development of a master plan for activities of a group of general surgeons serving two locations of a merged hospital system. The paper summarizes the main findings of the study and concludes with a discussion of results obtained with the new allocation procedure and with recommendations for future research.

  1. 1991 Acceptance priority ranking

    International Nuclear Information System (INIS)

    1991-12-01

    The Standard Contract for Disposal of Spent Nuclear Fuel and/or High- Level Radioactive Waste (10 CFR Part 961) that the Department of Energy (DOE) has executed with the owners and generators of civilian spent nuclear fuel requires annual publication of the Acceptance Priority Ranking (APR). The 1991 APR details the order in which DOE will allocate Federal waste acceptance capacity. As required by the Standard Contract, the ranking is based on the age of permanently discharged spent nuclear fuel (SNF), with the owners of the oldest SNF, on an industry-wide basis, given the highest priority. the 1991 APR will be the basis for the annual allocation of waste acceptance capacity to the Purchasers in the 1991 Annual Capacity Report (ACR), to be issued later this year. This document is based on SNF discharges as of December 31, 1990, and reflects Purchaser comments and corrections, as appropriate, to the draft APR issued on May 15, 1991

  2. An improved resource management model based on MDS

    Science.gov (United States)

    Yuan, Man; Sun, Changying; Li, Pengfei; Sun, Yongdong; He, Rui

    2005-11-01

    GRID technology provides a kind of convenient method for managing GRID resources. This service is so-called monitoring, discovering service. This method is proposed by Globus Alliance, in this GRID environment, all kinds of resources, such as computational resources, storage resources and other resources can be organized by MDS specifications. However, this MDS is a theory framework, particularly, in a small world intranet, in the case of limit of resources, the MDS has its own limitation. Based on MDS, an improved light method for managing corporation computational resources and storage resources is proposed in intranet(IMDS). Firstly, in MDS, all kinds of resource description information is stored in LDAP, it is well known although LDAP is a light directory access protocol, in practice, programmers rarely master how to access and store resource information into LDAP store, in such way, it limits MDS to be used. So, in intranet, these resources' description information can be stored in RDBMS, programmers and users can access this information by standard SQL. Secondly, in MDS, how to monitor all kinds of resources in GRID is not transparent for programmers and users. In such way, it limits its application scope, in general, resource monitoring method base on SNMP is widely employed in intranet, therefore, a kind of resource monitoring method based on SNMP is integrated into MDS. Finally, all kinds of resources in the intranet can be described by XML, and all kinds of resources' description information is stored in RDBMS, such as MySql, and retrieved by standard SQL, dynamic information for all kinds of resources can be sent to resource storage by SNMP, A prototype resource description, monitoring is designed and implemented in intranet.

  3. Minkowski metrics in creating universal ranking algorithms

    Directory of Open Access Journals (Sweden)

    Andrzej Ameljańczyk

    2014-06-01

    Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

  4. participation in Community Based Natural Resource Management

    African Journals Online (AJOL)

    user

    Rivers State University of Science and Technology, Port Harcourt, Nigeria. ... Resource Management Programme had empowered the beneficiaries in problem identification, ways of seeking for solution, project planning, implementation, ..... International Journal of Research, Innovations and Sustainable Development,.

  5. TVA GIS-based biomass resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Noon, C.E. [Univ. of Tennessee, Knoxville, TN (United States)

    1993-12-31

    The focus of this paper is a computer-based system for estimating the costs of supplying wood fuel. The system is being developed for the Tennessee Valley Authority and is referred to as the Biomass Resource Assessment Version One (BRAVO) system. The main objective in developing the BRAVO system is to assist TVA in estimating the costs for supplying wood fuel to any one of its twelve coal-fired plants. The BRAVO system is developed within a Geographic Information System (GIS) platform and is designed to allow a user to perform {open_quotes}what if{close_quotes} analyses related to the costs of wood fuel supply. Three types of wood fuel are considered in the BRAVO system: mill residues, logging residues and short-rotation woody crops (SRWC). Each type of wood fuel has unique economic and supply characteristics. The input data for the system includes the specific locations, amount, and prices of the various types of wood fuel throughout the TVA region. The system input is completed by data on political boundaries, power plant locations, road networks and a model for estimating transportation costs as a function of distance. The result is a comprehensive system which includes information on all possible wood fuel supply joints, demand points and product movement costs. In addition, the BRAVO system has been designed to allow a user to perform sensitivity analysis on a variety of supply system parameters. This will enable TVA to thoroughly investigate the financial impacts of issues such as increased competition for wood fuel, environmental policies, fuel taxes, and regional economic cycles.

  6. TVA GIS-based biomass resource assessment

    International Nuclear Information System (INIS)

    Noon, C.E.

    1993-01-01

    The focus of this paper is a computer-based system for estimating the costs of supplying wood fuel. The system is being developed for the Tennessee Valley Authority and is referred to as the Biomass Resource Assessment Version One (BRAVO) system. The main objective in developing the BRAVO system is to assist TVA in estimating the cost for supplying wood fuel to any one of its twelve coal-fired power plants. The BRAVO system is developed within a Geographic Information System (GIS) platform and is designed to allow a user to perform open-quotes what ifclose quotes analyses related to the costs of wood fuel supply. Three types of wood fuel are considered in the Bravo system: mill residues, logging residues and short-rotation woody crops (SRWC). Each type of wood fuel has unique economic and supply characteristics. The input data for the system includes the specific locations, amounts, and prices of the various types of wood fuel throughout the TVA region. The system input is completed by data on political boundaries, power plant locations, road networks and a model for estimating transportation costs as a function of distance. The result is a comprehensive system which includes information on all possible wood fuel supply points, demand points and product movement costs. In additions, the BRAVO system has been designed to allow a user to perform sensitivity analysis on a variety of supply system parameters. This will enable TVA to thoroughly investigate the financial impacts of issues such as increased competition for wood fuel, environmental policies, fuel taxes, and regional economic cycles

  7. Centrality based Document Ranking

    Science.gov (United States)

    2014-11-01

    support task. As it turned out, the results were very poor, which suggests that using a general purpose IR sytem in this way is not a good idea... Management on the Semantic Web, 2005. 15. P. Mika, T. Tudorache, A. Bernstein, C. Welty, C. A. Knoblock, D. Vrandecic, P. T. Groth, N. F. Noy, K. Janowicz...question- focused sentence retrieval. In HLT ’05: Proceedings of the conference on Hu- man Language Technology and Empirical Methods in Natural

  8. A study on the impact of parameter uncertainty on the emission-based ranking of transportation projects.

    Science.gov (United States)

    2014-01-01

    With the growing concern with air quality levels and, hence, the livability of urban regions in the nation, it has become increasingly common to incorporate vehicular emission considerations in the ranking of transportation projects. Network assignme...

  9. SRS: Site ranking system for hazardous chemical and radioactive waste

    International Nuclear Information System (INIS)

    Rechard, R.P.; Chu, M.S.Y.; Brown, S.L.

    1988-05-01

    This report describes the rationale and presents instructions for a site ranking system (SRS). SRS ranks hazardous chemical and radioactive waste sites by scoring important and readily available factors that influence risk to human health. Using SRS, sites can be ranked for purposes of detailed site investigations. SRS evaluates the relative risk as a combination of potentially exposed population, chemical toxicity, and potential exposure of release from a waste site; hence, SRS uses the same concepts found in a detailed assessment of health risk. Basing SRS on the concepts of risk assessment tends to reduce the distortion of results found in other ranking schemes. More importantly, a clear logic helps ensure the successful application of the ranking procedure and increases its versatility when modifications are necessary for unique situations. Although one can rank sites using a detailed risk assessment, it is potentially costly because of data and resources required. SRS is an efficient approach to provide an order-of-magnitude ranking, requiring only readily available data (often only descriptive) and hand calculations. Worksheets are included to make the system easier to understand and use. 88 refs., 19 figs., 58 tabs

  10. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  11. Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach1

    Science.gov (United States)

    Richardson, Rodney T.; Lin, Chia-Hua; Quijia, Juan O.; Riusech, Natalia S.; Goodell, Karen; Johnson, Reed M.

    2015-01-01

    Premise of the study: Difficulties inherent in microscopic pollen identification have resulted in limited implementation for large-scale studies. Metabarcoding, a relatively novel approach, could make pollen analysis less onerous; however, improved understanding of the quantitative capacity of various plant metabarcode regions and primer sets is needed to ensure that such applications are accurate and precise. Methods and Results: We applied metabarcoding, targeting the ITS2, matK, and rbcL loci, to characterize six samples of pollen collected by honey bees, Apis mellifera. Additionally, samples were analyzed by light microscopy. We found significant rank-based associations between the relative abundance of pollen types within our samples as inferred by the two methods. Conclusions: Our findings suggest metabarcoding data from plastid loci, as opposed to the ribosomal locus, are more reliable for quantitative characterization of pollen assemblages. Furthermore, multilocus metabarcoding of pollen may be more reliable than single-locus analyses, underscoring the need for discovering novel barcodes and barcode combinations optimized for molecular palynology. PMID:26649264

  12. Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models

    KAUST Repository

    El Gharamti, Mohamad; Hoteit, Ibrahim

    2014-01-01

    The accuracy of groundwater flow and transport model predictions highly depends on our knowledge of subsurface physical parameters. Assimilation of contaminant concentration data from shallow dug wells could help improving model behavior, eventually resulting in better forecasts. In this paper, we propose a joint state-parameter estimation scheme which efficiently integrates a low-rank extended Kalman filtering technique, namely the Singular Evolutive Extended Kalman (SEEK) filter, with the prominent complex-step method (CSM). The SEEK filter avoids the prohibitive computational burden of the Extended Kalman filter by updating the forecast along the directions of error growth only, called filter correction directions. CSM is used within the SEEK filter to efficiently compute model derivatives with respect to the state and parameters along the filter correction directions. CSM is derived using complex Taylor expansion and is second order accurate. It is proven to guarantee accurate gradient computations with zero numerical round-off errors, but requires complexifying the numerical code. We perform twin-experiments to test the performance of the CSM-based SEEK for estimating the state and parameters of a subsurface contaminant transport model. We compare the efficiency and the accuracy of the proposed scheme with two standard finite difference-based SEEK filters as well as with the ensemble Kalman filter (EnKF). Assimilation results suggest that the use of the CSM in the context of the SEEK filter may provide up to 80% more accurate solutions when compared to standard finite difference schemes and is competitive with the EnKF, even providing more accurate results in certain situations. We analyze the results based on two different observation strategies. We also discuss the complexification of the numerical code and show that this could be efficiently implemented in the context of subsurface flow models. © 2013 Elsevier B.V.

  13. Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models

    KAUST Repository

    El Gharamti, Mohamad

    2014-02-01

    The accuracy of groundwater flow and transport model predictions highly depends on our knowledge of subsurface physical parameters. Assimilation of contaminant concentration data from shallow dug wells could help improving model behavior, eventually resulting in better forecasts. In this paper, we propose a joint state-parameter estimation scheme which efficiently integrates a low-rank extended Kalman filtering technique, namely the Singular Evolutive Extended Kalman (SEEK) filter, with the prominent complex-step method (CSM). The SEEK filter avoids the prohibitive computational burden of the Extended Kalman filter by updating the forecast along the directions of error growth only, called filter correction directions. CSM is used within the SEEK filter to efficiently compute model derivatives with respect to the state and parameters along the filter correction directions. CSM is derived using complex Taylor expansion and is second order accurate. It is proven to guarantee accurate gradient computations with zero numerical round-off errors, but requires complexifying the numerical code. We perform twin-experiments to test the performance of the CSM-based SEEK for estimating the state and parameters of a subsurface contaminant transport model. We compare the efficiency and the accuracy of the proposed scheme with two standard finite difference-based SEEK filters as well as with the ensemble Kalman filter (EnKF). Assimilation results suggest that the use of the CSM in the context of the SEEK filter may provide up to 80% more accurate solutions when compared to standard finite difference schemes and is competitive with the EnKF, even providing more accurate results in certain situations. We analyze the results based on two different observation strategies. We also discuss the complexification of the numerical code and show that this could be efficiently implemented in the context of subsurface flow models. © 2013 Elsevier B.V.

  14. Ranking environmental liabilities at a petroleum refinery

    International Nuclear Information System (INIS)

    Lupo, M.

    1995-01-01

    A new computer model is available to allow the management of a petroleum refinery to prioritize environmental action and construct a holistic approach to remediation. A large refinery may have numerous solid waste management units regulated by the Resource Conservation and Recovery Act (RCRA), as well as process units that emit hazardous chemicals into the environment. These sources can impact several environmental media, potentially including the air, the soil, the groundwater, the unsaturated zone water, and surface water. The number of chemicals of concern may be large. The new model is able to rank the sources by considering the impact of each chemical in each medium from each source in terms of concentration, release rate, and a weighted index based on toxicity. In addition to environmental impact, the sources can be ranked in three other ways: (1) by cost to remediate, (2) by environmental risk reduction caused by the remediation in terms of the decreases in release rate, concentration, and weighted index, and (3) by cost-benefit, which is the environmental risk reduction for each source divided by the cost of the remedy. Ranking each unit in the refinery allows management to use its limited environmental resources in a pro-active strategic manner that produces long-term results, rather than in reactive, narrowly focused, costly, regulatory-driven campaigns that produce only short-term results

  15. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  16. Ranking Support Vector Machine with Kernel Approximation

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2017-01-01

    Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  17. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

    Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  18. Phenomena identification ranking table and knowledge base gaps and needs for the modular high-temperature gas-cooled reactor

    International Nuclear Information System (INIS)

    Tokuhiro, Akira; Potirniche, Gabriel; Rink, Karl

    2009-01-01

    The U.S. is developing a modular high-temperature gas-cooled reactor (MHTGR) under the Next Generation Nuclear Plant (NGNP); also known as the Very High Temperature Reactor (VHTR). The generic MHTGR is a graphite-moderated, gas-cooled reactor (GCR) of either a prismatic modular (block-type, PMR) or pebble-bed (PBR) core configuration. The pebble-bed design requires new attention with respect to neutronics, materials, thermal hydraulic, safety and licensing relative to the set of phenomena and engineering analyses associated with the current fleet of legacy LWRs. In fact, the relative knowledge and experiential base on gas reactors is small in comparison to the LWR. There is a dated body of knowledge from some 25+ years ago on GCRs; recently there is a renewed interest. Thus in the present design and development phase of the NGNP/VHTR, there are relevant thermohydraulic safety issues surrounding the MHTGR with issues impacting foremost the design review process. A common phenomena with respect to PMR and PBR core design, is that concerning 'graphite dust' and its interaction and transport with potential fission products (FP) that may be present within the graphite and subsequently in the primary system. The nature of the graphite and FPs, when circulated or transported in the primary, and possibly beyond, is of concern as potentially an relevant 'source term' (radionuclide inventory) of the MHTGR. Based on NUREG/CR-6944, Volumes 1-5, the author briefly describes the state-of-the art knowledge base on graphite dust and FP transport with respect to the anticipated design of the MHTGR. In addition, from the Phenomena Identification and Ranking Tables (PIRTs) developed in these reports we concurrently identify and describe 'gaps and needs' of the knowledge base. That is, we also present the knowledge base gaps and needs with respect to the following: 1) R and D needs relative to PIRTs, 2) (experimental) database needs relative to PIRTs, and 3) simulation and modeling

  19. Geothermal-resource verification for Air Force bases

    Energy Technology Data Exchange (ETDEWEB)

    Grant, P.R. Jr.

    1981-06-01

    This report summarizes the various types of geothermal energy reviews some legal uncertainties of the resource and then describes a methodology to evaluate geothermal resources for applications to US Air Force bases. Estimates suggest that exploration costs will be $50,000 to $300,000, which, if favorable, would lead to drilling a $500,000 exploration well. Successful identification and development of a geothermal resource could provide all base, fixed system needs with an inexpensive, renewable energy source.

  20. Virtual network embedding in cross-domain network based on topology and resource attributes

    Science.gov (United States)

    Zhu, Lei; Zhang, Zhizhong; Feng, Linlin; Liu, Lilan

    2018-03-01

    Aiming at the network architecture ossification and the diversity of access technologies issues, this paper researches the cross-domain virtual network embedding algorithm. By analysing the topological attribute from the local and global perspective of nodes in the virtual network and the physical network, combined with the local network resource property, we rank the embedding priority of the nodes with PCA and TOPSIS methods. Besides, the link load distribution is considered. Above all, We proposed an cross-domain virtual network embedding algorithm based on topology and resource attributes. The simulation results depicts that our algorithm increases the acceptance rate of multi-domain virtual network requests, compared with the existing virtual network embedding algorithm.

  1. Ranking of concern, based on environmental indexes, for pharmaceutical and personal care products: an application to the Spanish case.

    Science.gov (United States)

    Ortiz de García, Sheyla; Pinto, Gilberto Pinto; García-Encina, Pedro A; Irusta Mata, Rubén I

    2013-11-15

    A wide range of Pharmaceuticals and Personal Care Products (PPCPs) are present in the environment, and many of their adverse effects are unknown. The emergence of new compounds or changes in regulations have led to dynamical studies of occurrence, impact and treatment, which consider geographical areas and trends in consumption and innovation in the pharmaceutical industry. A Quantitative study of Structure-Activity Relationship ((Q)SAR) was performed to assess the possible adverse effects of ninety six PPCPs and metabolites with negligible experimental data and establish a ranking of concern, which was supported by the EPA EPI Suite™ interface. The environmental and toxicological indexes, the persistence (P), the bioaccumulation (B), the toxicity (T) (extensive) and the occurrence in Spanish aquatic environments (O) (intensive) were evaluated. The most hazardous characteristics in the largest number of compounds were generated by the P index, followed by the T and B indexes. A high number of metabolites has a concern score equal to or greater than their parent compounds. Three PBT and OPBT rankings of concern were proposed using the total and partial ranking method (supported by a Hasse diagram) by the Decision Analysis by Ranking Techniques (DART) tool, which was recently recommended by the European Commission. An analysis of the sensibility of the relative weights of these indexes has been conducted. Hormones, antidepressants (and their metabolites), blood lipid regulators and all of the personal care products considered in this study were at the highest levels of risk according to the PBT and OPBT total rankings. Furthermore, when the OPBT partial ranking was performed, X-ray contrast media, H2 blockers and some antibiotics were included at the highest level of concern. It is important to improve and incorporate useful indexes for the predicted environmental impact of PPCPs and metabolites and thus focus experimental analysis on the compounds that require

  2. A scenario based approach for flexible resource loading under uncertainty

    NARCIS (Netherlands)

    Wullink, Gerhard; Gademann, Noud; Hans, Elias W.; van Harten, Aart

    2003-01-01

    Order acceptance decisions in manufacture-to-order environments are often made based on incomplete or uncertain information. To promise reliable due dates and to manage resource capacity adequately, resource capacity loading is an indispensable supporting tool. We propose a scenario based approach

  3. A new mutually reinforcing network node and link ranking algorithm.

    Science.gov (United States)

    Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E

    2015-10-23

    This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

  4. A new mutually reinforcing network node and link ranking algorithm

    Science.gov (United States)

    Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

    2015-10-01

    This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

  5. A new mutually reinforcing network node and link ranking algorithm

    Science.gov (United States)

    Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

    2015-01-01

    This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity. PMID:26492958

  6. Evidence-based human resource management: a study of nurse leaders' resource allocation.

    Science.gov (United States)

    Fagerström, Lisbeth

    2009-05-01

    The aims were to illustrate how the RAFAELA system can be used to facilitate evidence-based human resource management. The theoretical framework of the RAFAELA system is based on a holistic view of humankind and a view of leadership founded on human resource management. Nine wards from three central hospitals in Finland participated in the study. The data, stemming from 2006-2007, were taken from the critical indicators (ward-related and nursing intensity information) for national benchmarking used in the RAFAELA system. The data were analysed descriptively. The daily nursing resources per classified patient ratio is a more specific method of measurement than the nurse-to-patient ratio. For four wards, the nursing intensity per nurse surpassed the optimal level 34% to 62.2% of days. Resource allocation was clearly improved in that a better balance between patients' care needs and available nursing resources was maintained. The RAFAELA system provides a rational, systematic and objective foundation for evidence-based human resource management. Data from a systematic use of the RAFAELA system offer objective facts and motives for evidence-based decision making in human resource management, and will therefore enhance the nurse leaders' evidence and scientific based way of working.

  7. Universal scaling in sports ranking

    International Nuclear Information System (INIS)

    Deng Weibing; Li Wei; Cai Xu; Bulou, Alain; Wang Qiuping A

    2012-01-01

    Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

  8. Managing the relationship between strategic resources and competitive priorities through the resource-based view

    Directory of Open Access Journals (Sweden)

    Cláudia Fabiana Gohr

    2015-06-01

    Full Text Available Firms should develop and improve strategic resources that are important for the competitive priorities, especially those that are important to customers. Using resource-based view of the firm as a theoretical perspective, this paper aims to analyze how strategic resources can contribute to the competitive priorities of an organization that operates in the logistic sector. The research method used was the case study using as the main technique of data collection semi-structured and structured interviews; and, systematic observations. The resources that contribute effectively to competitive priorities that need improvement are sales control, loyal customer base, partners experience and agile feedback to customers. However, only the experience of the partners provides to the company sustainable competitive advantage. Others resources identified in the field research provide only a competitive parity, despite this, support important competitive priorities.

  9. A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

    Directory of Open Access Journals (Sweden)

    Vassal Aurélien

    2008-01-01

    Full Text Available Abstract Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM. Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with

  10. Local constructions of gender-based violence amongst IDPs in northern Uganda: analysis of archival data collected using a gender- and age-segmented participatory ranking methodology.

    Science.gov (United States)

    Ager, Alastair; Bancroft, Carolyn; Berger, Elizabeth; Stark, Lindsay

    2018-01-01

    Gender-based violence (GBV) is a significant problem in conflict-affected settings. Understanding local constructions of such violence is crucial to developing preventive and responsive interventions to address this issue. This study reports on a secondary analysis of archived data collected as part of formative qualitative work - using a group participatory ranking methodology (PRM) - informing research on the prevalence of GBV amongst IDPs in northern Uganda in 2006. Sixty-four PRM group discussions were held with women, with men, with girls (aged 14 to 18 years), and with boys (aged 14 to 18 years) selected on a randomized basis across four internally displaced persons (IDP) camps in Lira District. Discussions elicited problems facing women in the camps, and - through structured participatory methods - consensus ranking of their importance and narrative accounts explaining these judgments. Amongst forms of GBV faced by women, rape was ranked as the greatest concern amongst participants (with a mean problem rank of 3.4), followed by marital rape (mean problem rank of 4.5) and intimate partner violence (mean problem rank of 4.9). Girls ranked all forms of GBV as higher priority concerns than other participants. Discussions indicated that these forms of GBV were generally considered normalized within the camp. Gender roles and power, economic deprivation, and physical and social characteristics of the camp setting emerged as key explanatory factors in accounts of GBV prevalence, although these played out in different ways with respect to differing forms of violence. All groups acknowledged GBV to represent a significant threat - among other major concerns such as transportation, water, shelter, food and security - for women residing in the camps. Given evidence of the significantly higher risk in the camp of intimate partner violence and marital rape, the relative prominence of the issue of rape in all rankings suggests normalization of violence within the home

  11. Ranking Baltic States Researchers

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2017-10-01

    Full Text Available In this article, using the h-index and the total number of citations, the best 10 Lithuanian, Latvian and Estonian researchers from several disciplines are ranked. The list may be formed based on the h-index and the total number of citations, given in Web of Science, Scopus, Publish or Perish Program and Google Scholar database. Data for the first 10 researchers are presented. Google Scholar is the most complete. Therefore, to define a single indicator, h-index calculated by Google Scholar may be a good and simple one. The author chooses the Google Scholar database as it is the broadest one.

  12. Unique Nanoparticle Optical Properties Confound Fluorescent Based Assays Widely Employed in Their In Vitro Toxicity Screening and Ranking

    Science.gov (United States)

    Nanoparticles (NPs) are novel materials having at least one dimension less than 100 nm and display unique physicochemical properties due to their nanoscale size. An emphasis has been placed on developing high throughput screening (HTS) assays to characterize and rank the toxiciti...

  13. Efficient Resources Provisioning Based on Load Forecasting in Cloud

    Directory of Open Access Journals (Sweden)

    Rongdong Hu

    2014-01-01

    Full Text Available Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application’s actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements.

  14. Resource allocation in smart homes based on Banker's algorithm

    NARCIS (Netherlands)

    Virag, A.; Bogdan, S.

    2011-01-01

    This paper proposes a method for improved energy management in smart homes by means of resource allocation. For this purpose, a Banker's algorithm based strategy has been developed. It is used to control the system and decide which of the given processes should be provided with resources at the

  15. Consumer-resource stoichiometry in detritus-based streams

    Science.gov (United States)

    Wyatt F. Cross; Jonathan P. Benstead; Amy D. Rosemond; J. Bruce Wallace

    2003-01-01

    Stoichiometric relationships between consumers and resources in detritus-based ecosystems have received little attention, despite the importance of detritus in most food webs. We analysed carbon (C), nitrogen (N), and phosphorus (P) content of invertebrate consumers, and basal food resources in two forested headwater streams (one reference and the other nutrient-...

  16. Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

    Science.gov (United States)

    Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

    2014-04-01

    Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

  17. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Directory of Open Access Journals (Sweden)

    Dániel Bánky

    Full Text Available Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks that compensates for the low degree (non-hub vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well, but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus, and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures

  18. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Science.gov (United States)

    Bánky, Dániel; Iván, Gábor; Grolmusz, Vince

    2013-01-01

    Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks) that compensates for the low degree (non-hub) vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges) of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well), but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus), and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures importance in the

  19. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-04-17

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

  20. Resources available for school based mental health services in ...

    African Journals Online (AJOL)

    Resources available for school based mental health services in Enugu urban and head teachers' knowledge of childhood mental health problems. ... PROMOTING ACCESS TO AFRICAN RESEARCH. AFRICAN JOURNALS ONLINE (AJOL) ...

  1. NOAA's Estuarine Living Marine Resources (ELMR) Data Base

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In 1985, NOAA launched the Estuarine Living Marine Resources (ELMR) Program to develop a consistent data base on the distribution, relative abundance, and life...

  2. Selection of the open pit mining cut-off grade strategy under price uncertainty using a risk based multi-criteria ranking system / Wybór strategii określania warunku opłacalności wydobycia w kopalniach odkrywkowych w warunkach niepewności cen w oparciu o wielokryterialny system rankingowy z uwzględnieniem czynników ryzyka

    Science.gov (United States)

    Azimi, Yousue; Osanloo, Montza; Esfahanipour, Akbar

    2012-12-01

    Cut-off Grade Strategy (COGS) is a concept that directly influences the financial, technical, economic, environmental, and legal issues in relation to exploitation of a mineral resource. A decision making system is proposed to select the best technically feasible COGS under price uncertainty. In the proposed system both the conventional discounted cash flow and modern simulation based real option valuations are used to evaluate the alternative strategies. Then the conventional expected value criterion and a multiple criteria ranking system were used to rank the strategies based on the two valuation methods. In the multiple criteria ranking system besides the expected value other stochastic orders expressing abilities of strategies in producing extra profits, minimizing losses and achieving the predefined goals of the exploitation strategy are considered. Finally, the best strategy is selected based on the overall average rank of strategies through all ranking systems. The proposed system was examined using the data of Sungun Copper Mine. To assess the merits of the alternatives better, ranking process was done at both high (prevailing economic condition) and low price conditions. Ranking results revealed that at different price conditions and valuation methods, different results would be obtained. It is concluded that these differences are due to the different behavior of the embedded option to close the mine early, which is more likely to be exercised under low price condition rather than high price condition. The proposed system would enhance the quality of decision making process by providing a more informative and certain platform for project evaluation.

  3. CBM Resources/reserves classification and evaluation based on PRMS rules

    Science.gov (United States)

    Fa, Guifang; Yuan, Ruie; Wang, Zuoqian; Lan, Jun; Zhao, Jian; Xia, Mingjun; Cai, Dechao; Yi, Yanjing

    2018-02-01

    This paper introduces a set of definitions and classification requirements for coalbed methane (CBM) resources/reserves, based on Petroleum Resources Management System (PRMS). The basic CBM classification criterions of 1P, 2P, 3P and contingent resources are put forward from the following aspects: ownership, project maturity, drilling requirements, testing requirements, economic requirements, infrastructure and market, timing of production and development, and so on. The volumetric method is used to evaluate the OGIP, with focuses on analyses of key parameters and principles of the parameter selection, such as net thickness, ash and water content, coal rank and composition, coal density, cleat volume and saturation and absorbed gas content etc. A dynamic method is used to assess the reserves and recovery efficiency. Since the differences in rock and fluid properties, displacement mechanism, completion and operating practices and wellbore type resulted in different production curve characteristics, the factors affecting production behavior, the dewatering period, pressure build-up and interference effects were analyzed. The conclusion and results that the paper achieved can be used as important references for reasonable assessment of CBM resources/reserves.

  4. Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources

    Directory of Open Access Journals (Sweden)

    Paweł Kędzia

    2015-12-01

    Full Text Available Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources Lexical resources can be applied in many different Natural Language Engineering tasks, but the most fundamental task is the recognition of word senses used in text contexts. The problem is difficult, not yet fully solved and different lexical resources provided varied support for it. Polish CLARIN lexical semantic resources are based on the plWordNet — a very large wordnet for Polish — as a central structure which is a basis for linking together several resources of different types. In this paper, several Word Sense Disambiguation (henceforth WSD methods developed for Polish that utilise plWordNet are discussed. Textual sense descriptions in the traditional lexicon can be compared with text contexts using Lesk’s algorithm in order to find best matching senses. In the case of a wordnet, lexico-semantic relations provide the main description of word senses. Thus, first, we adapted and applied to Polish a WSD method based on the Page Rank. According to it, text words are mapped on their senses in the plWordNet graph and Page Rank algorithm is run to find senses with the highest scores. The method presents results lower but comparable to those reported for English. The error analysis showed that the main problems are: fine grained sense distinctions in plWordNet and limited number of connections between words of different parts of speech. In the second approach plWordNet expanded with the mapping onto the SUMO ontology concepts was used. Two scenarios for WSD were investigated: two step disambiguation and disambiguation based on combined networks of plWordNet and SUMO. In the former scenario, words are first assigned SUMO concepts and next plWordNet senses are disambiguated. In latter, plWordNet and SUMO are combined in one large network used next for the disambiguation of senses. The additional knowledge sources used in WSD improved the performance

  5. Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

    Science.gov (United States)

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

    Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

  6. Power System Event Ranking Using a New Linear Parameter-Varying Modeling with a Wide Area Measurement System-Based Approach

    Directory of Open Access Journals (Sweden)

    Mohammad Bagher Abolhasani Jabali

    2017-07-01

    Full Text Available Detecting critical power system events for Dynamic Security Assessment (DSA is required for reliability improvement. The approach proposed in this paper investigates the effects of events on dynamic behavior during nonlinear system response while common approaches use steady-state conditions after events. This paper presents some new and enhanced indices for event ranking based on time-domain simulation and polytopic linear parameter-varying (LPV modeling of a power system. In the proposed approach, a polytopic LPV representation is generated via linearization about some points of the nonlinear dynamic behavior of power system using wide-area measurement system (WAMS concepts and then event ranking is done based on the frequency response of the system models on the vertices. Therefore, the nonlinear behaviors of the system in the time of fault occurrence are considered for events ranking. The proposed algorithm is applied to a power system using nonlinear simulation. The comparison of the results especially in different fault conditions shows the advantages of the proposed approach and indices.

  7. Ranking Hospitals Based on Colon Surgery and Abdominal Hysterectomy Surgical Site Infection Outcomes: Impact of Limiting Surveillance to the Operative Hospital.

    Science.gov (United States)

    Yokoe, Deborah S; Avery, Taliser R; Platt, Richard; Kleinman, Ken; Huang, Susan S

    2018-03-16

    Hospital-specific surgical site infection (SSI) performance following colon surgery and abdominal hysterectomies can impact hospitals' relative rankings around quality metrics used to determine financial penalties. Current SSI surveillance largely focuses on SSI detected at the operative hospital. Retrospective cohort study to assess the impact on hospitals' relative SSI performance rankings when SSI detected at non-operative hospitals are included. We utilized data from a California statewide hospital registry to assess for evidence of SSI following colon surgery or abdominal hysterectomies performed 3/1/2011-11/30/2013 using previously validated claims-based SSI surveillance methods. Risk-adjusted hospital-specific rankings based on SSI detected at operative hospitals versus any California hospital were generated. Among 60,059 colon surgeries at 285 hospitals and 64,918 abdominal hysterectomies at 270 hospitals, 5,921 (9.9%) colon surgeries and 1,481 (2.3%) abdominal hysterectomies received a diagnosis code for SSI within the 30 days following surgery. 7.2% of colon surgery and 13.4% of abdominal hysterectomy SSI would have been missed by operative hospital surveillance alone. The proportion of individual hospital's SSI detected during hospitalizations at other hospitals varied widely. Including non-operative hospital SSI resulted in improved relative ranking of 11 (3.9%) colon surgery and 13 (4.8%) hysterectomy hospitals so that they were no longer in the worst performing quartile, mainly among hospitals with relatively high surgical volumes. Standard SSI surveillance that mainly focuses on infections detected at the operative hospital causes varying degrees of SSI under-estimation, leading to inaccurate assignment or avoidance of financial penalties for approximately one in eleven to sixteen hospitals.

  8. Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2011-10-31

    The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain

  9. Natural hydrocarbon gases in Canada: the resource base

    International Nuclear Information System (INIS)

    Osadetz, K.G.

    1997-01-01

    The Geological Survey of Canada (GSC) has an ongoing national hydrocarbon resource assessment project which examines, characterizes and quantifies the hydrocarbon resource potential of Canada. In this paper the distribution, characteristics and sizes of conventional and unconventional natural gas resources in Canada are summarized. Four topics were addressed: (1) the origins of conventional and unconventional natural hydrocarbon gases in Canada, (2) the resource assessment techniques used at the GSC, with emphasis on predicting undiscovered reserves, (3) the setting, distribution and size of the conventional natural gas endowment of Canada in a geographic and geological context, and (4) the indications of unconventional natural gas resource endowment in Canada. Conventional in-place natural gas resources for Canada was estimated at 26.8 trillion cubic metres of which 54 per cent comes from the Western Canada Sedimentary Basin. The national inventory of unconventional in-place gas resource is 3,460 trillion cubic metres. At current rates of production, the expected life expectancy for the in-place conventional natural gas resource base was estimated to be about 150 years. 1 tab., 9 figs

  10. Analysis and research of influence factors ranking of fuzzy language translation accuracy in literary works based on catastrophe progression method

    Directory of Open Access Journals (Sweden)

    Wei Dong

    2017-02-01

    Full Text Available This paper researches the problem of decline in translation accuracy caused by language “vagueness” in literary translation, and proposes to use the catastrophe model for importance ranking of various factors affecting the fuzzy language translation accuracy in literary works, and finally gives out the order of factors to be considered before translation. The multi-level evaluation system can be used to construct the relevant catastrophe progression model, and the normalization formula can be used to calculate the relative membership degree of each system and evaluation index, and make evaluation combined with the evaluation criteria table. The results show that, in the fuzzy language translation, in order to improve the translation accuracy, there is a need to consider the indicators ranking: A2 fuzzy language context → A1 words attribute → A3 specific meaning of digital words; B2 fuzzy semantics, B3 blur color words → B1 multiple meanings of words → B4 fuzzy digital words; C3 combination with context and cultural background, C4 specific connotation of color words → C1 combination with words emotion, C2 selection of words meaning → C5 combination with digits and language background.

  11. Incorporation of Socio-Economic Features' Ranking in Multicriteria Analysis Based on Ecosystem Services for Marine Protected Area Planning.

    Directory of Open Access Journals (Sweden)

    Michelle E Portman

    Full Text Available Developed decades ago for spatial choice problems related to zoning in the urban planning field, multicriteria analysis (MCA has more recently been applied to environmental conflicts and presented in several documented cases for the creation of protected area management plans. Its application is considered here for the development of zoning as part of a proposed marine protected area management plan. The case study incorporates specially-explicit conservation features while considering stakeholder preferences, expert opinion and characteristics of data quality. It involves the weighting of criteria using a modified analytical hierarchy process. Experts ranked physical attributes which include socio-economically valued physical features. The parameters used for the ranking of (physical attributes important for socio-economic reasons are derived from the field of ecosystem services assessment. Inclusion of these feature values results in protection that emphasizes those areas closest to shore, most likely because of accessibility and familiarity parameters and because of data biases. Therefore, other spatial conservation prioritization methods should be considered to supplement the MCA and efforts should be made to improve data about ecosystem service values farther from shore. Otherwise, the MCA method allows incorporation of expert and stakeholder preferences and ecosystem services values while maintaining the advantages of simplicity and clarity.

  12. Cognitive radio resource allocation based on coupled chaotic genetic algorithm

    International Nuclear Information System (INIS)

    Zu Yun-Xiao; Zhou Jie; Zeng Chang-Chang

    2010-01-01

    A coupled chaotic genetic algorithm for cognitive radio resource allocation which is based on genetic algorithm and coupled Logistic map is proposed. A fitness function for cognitive radio resource allocation is provided. Simulations are conducted for cognitive radio resource allocation by using the coupled chaotic genetic algorithm, simple genetic algorithm and dynamic allocation algorithm respectively. The simulation results show that, compared with simple genetic and dynamic allocation algorithm, coupled chaotic genetic algorithm reduces the total transmission power and bit error rate in cognitive radio system, and has faster convergence speed

  13. Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory

    Science.gov (United States)

    Rai, Prashant; Sargsyan, Khachik; Najm, Habib; Hermes, Matthew R.; Hirata, So

    2017-09-01

    A new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a relatively short sum of products of low-dimensional integrals. The decomposition is achieved by the alternating least squares (ALS) algorithm, requiring only a small number of single-point energy evaluations. Therefore, it eradicates a force-constant evaluation as the hotspot of many quantum dynamics simulations and also possibly lifts the curse of dimensionality. This general method is applied to the anharmonic vibrational zero-point and transition energy calculations of molecules using the second-order diagrammatic vibrational many-body Green's function (XVH2) theory with a harmonic-approximation reference. In this application, high dimensional PES and Green's functions are both subjected to a low-rank decomposition. Evaluating the molecular integrals over a low-rank PES and Green's functions as sums of low-dimensional integrals using the Gauss-Hermite quadrature, this canonical-tensor-decomposition-based XVH2 (CT-XVH2) achieves an accuracy of 0.1 cm-1 or higher and nearly an order of magnitude speedup as compared with the original algorithm using force constants for water and formaldehyde.

  14. Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory

    International Nuclear Information System (INIS)

    Rai, Prashant; Sargsyan, Khachik; Najm, Habib; Hermes, Matthew R.; Hirata, So

    2017-01-01

    Here, a new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a relatively short sum of products of low-dimensional integrals. The decomposition is achieved by the alternating least squares (ALS) algorithm, requiring only a small number of single-point energy evaluations. Therefore, it eradicates a force-constant evaluation as the hotspot of many quantum dynamics simulations and also possibly lifts the curse of dimensionality. This general method is applied to the anharmonic vibrational zero-point and transition energy calculations of molecules using the second-order diagrammatic vibrational many-body Green's function (XVH2) theory with a harmonic-approximation reference. In this application, high dimensional PES and Green's functions are both subjected to a low-rank decomposition. Evaluating the molecular integrals over a low-rank PES and Green's functions as sums of low-dimensional integrals using the Gauss–Hermite quadrature, this canonical-tensor-decomposition-based XVH2 (CT-XVH2) achieves an accuracy of 0.1 cm -1 or higher and nearly an order of magnitude speedup as compared with the original algorithm using force constants for water and formaldehyde.

  15. Science-based natural resource management decisions: what are they?

    Science.gov (United States)

    T.J. Mills; T.M. Quigley; F.J. Everest

    2001-01-01

    While many people interested in natural resources management propose science-based decisions, it is not clear what “science-based” means. Science-based decisions are those that result from the full and complete consideration of the relevant science information. We offer five guidelines to focus the scientist’s contributions to science-based decisionmaking and use the...

  16. Adaptive capacity and community-based natural resource management.

    Science.gov (United States)

    Armitage, Derek

    2005-06-01

    Why do some community-based natural resource management strategies perform better than others? Commons theorists have approached this question by developing institutional design principles to address collective choice situations, while other analysts have critiqued the underlying assumptions of community-based resource management. However, efforts to enhance community-based natural resource management performance also require an analysis of exogenous and endogenous variables that influence how social actors not only act collectively but do so in ways that respond to changing circumstances, foster learning, and build capacity for management adaptation. Drawing on examples from northern Canada and Southeast Asia, this article examines the relationship among adaptive capacity, community-based resource management performance, and the socio-institutional determinants of collective action, such as technical, financial, and legal constraints, and complex issues of politics, scale, knowledge, community and culture. An emphasis on adaptive capacity responds to a conceptual weakness in community-based natural resource management and highlights an emerging research and policy discourse that builds upon static design principles and the contested concepts in current management practice.

  17. CONSTRUCTION OF REGULAR LDPC LIKE CODES BASED ON FULL RANK CODES AND THEIR ITERATIVE DECODING USING A PARITY CHECK TREE

    Directory of Open Access Journals (Sweden)

    H. Prashantha Kumar

    2011-09-01

    Full Text Available Low density parity check (LDPC codes are capacity-approaching codes, which means that practical constructions exist that allow the noise threshold to be set very close to the theoretical Shannon limit for a memory less channel. LDPC codes are finding increasing use in applications like LTE-Networks, digital television, high density data storage systems, deep space communication systems etc. Several algebraic and combinatorial methods are available for constructing LDPC codes. In this paper we discuss a novel low complexity algebraic method for constructing regular LDPC like codes derived from full rank codes. We demonstrate that by employing these codes over AWGN channels, coding gains in excess of 2dB over un-coded systems can be realized when soft iterative decoding using a parity check tree is employed.

  18. On Page Rank

    NARCIS (Netherlands)

    Hoede, C.

    In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

  19. On Rank and Nullity

    Science.gov (United States)

    Dobbs, David E.

    2012-01-01

    This note explains how Emil Artin's proof that row rank equals column rank for a matrix with entries in a field leads naturally to the formula for the nullity of a matrix and also to an algorithm for solving any system of linear equations in any number of variables. This material could be used in any course on matrix theory or linear algebra.

  20. Hitting the Rankings Jackpot

    Science.gov (United States)

    Chapman, David W.

    2008-01-01

    Recently, Samford University was ranked 27th in the nation in a report released by "Forbes" magazine. In this article, the author relates how the people working at Samford University were surprised at its ranking. Although Samford is the largest privately institution in Alabama, its distinguished academic achievements aren't even…

  1. Consistent ranking of volatility models

    DEFF Research Database (Denmark)

    Hansen, Peter Reinhard; Lunde, Asger

    2006-01-01

    We show that the empirical ranking of volatility models can be inconsistent for the true ranking if the evaluation is based on a proxy for the population measure of volatility. For example, the substitution of a squared return for the conditional variance in the evaluation of ARCH-type models can...... variance in out-of-sample evaluations rather than the squared return. We derive the theoretical results in a general framework that is not specific to the comparison of volatility models. Similar problems can arise in comparisons of forecasting models whenever the predicted variable is a latent variable....

  2. PageRank (II): Mathematics

    African Journals Online (AJOL)

    maths/stats

    ... GAUSS SEIDEL'S. NUMERICAL ALGORITHMS IN PAGE RANK ANALYSIS. ... The convergence is guaranteed, if the absolute value of the largest eigen ... improved Gauss-Seidel iteration algorithm, based on the decomposition. U. L. D. M. +. +. = ..... This corresponds to determine the eigen vector of T with eigen value 1.

  3. Using centrality to rank web snippets

    NARCIS (Netherlands)

    Jijkoun, V.; de Rijke, M.; Peters, C.; Jijkoun, V.; Mandl, T.; Müller, H.; Oard, D.W.; Peñas, A.; Petras, V.; Santos, D.

    2008-01-01

    We describe our participation in the WebCLEF 2007 task, targeted at snippet retrieval from web data. Our system ranks snippets based on a simple similarity-based centrality, inspired by the web page ranking algorithms. We experimented with retrieval units (sentences and paragraphs) and with the

  4. Chunk-Based Energy Efficient Resource Allocation in OFDMA Systems

    Directory of Open Access Journals (Sweden)

    Yong Li

    2013-01-01

    Full Text Available Energy efficiency (EE capacity analysis of the chunk-based resource allocation is presented by considering the minimum spectrum efficiency (SE constraint in downlink multiuser orthogonal frequency division multiplexing (OFDM systems. Considering the minimum SE requirement, an optimization problem to maximize EE with limited transmit power is formulated over frequency selective channels. Based on this model, a low-complexity energy efficient resource allocation is proposed. The effects of system parameters, such as the average channel gain-to-noise ratio (CNR and the number of subcarriers per chunk, are evaluated. Numerical results demonstrate the effectiveness of the proposed scheme for balancing the EE and SE.

  5. The Servitization of Manufacturing: A Resource-Based Perspective

    DEFF Research Database (Denmark)

    Yang, Cheng; Boer, Harry; Johansen, John

    2010-01-01

    The traditional focus of manufacturing strategy is tremendously impacted by the emergence of servitization as a new empirical phenomenon and the resource-based view (RBV) as a (relatively) new theoretical perspective. In order to understand their influence, this paper firstly tracks the evolution....... Based on the case analyses and inspired by open source software (OSS) and open innovation, a new, open and capability (development) based role of manufacturing is suggested....

  6. Available web-based teaching resources for health care professionals on screening for oral cancer

    Science.gov (United States)

    Varela-Centelles, Pablo; Insua, Angel; Warnakulasuriya, Saman; Rapidis, Alexander; Diz, Pedro; Seoane, Juan

    2015-01-01

    Objectives: To identify websites with adequate information on oral cancer screening for healthcare professionals (HCPs) and to assess both their quality and contents. Study Design: Websites were identified using Google and HON medical professional search engines using the terms “screening for oral cancer”. The first 100 sites retrieved by each engine were analysed using the DISCERN questionnaire (reliability), the V instrument (contents on oral cancer) and further by the Flesch-Kinkaid Reading Grade Level and the Flesch Reading Ease (readability). Results: The overall rating showed minimal shortcomings in the quality of the information in the websites. The coverage and correctness of information on “visual examination” was rated as fair/good, whereas updating of contents resulted very variable (eg: 81% for visual examination and 18.2% for molecular biomarkers). These results permitted to rank the websites housing relevant information for oral cancer. Top ranking websites were affiliated to the Oral Cancer Foundation (USA), WHO Collaborating Centre for oral cancer (UK) whose webpage is entitled “Oral Cancer Education and Research”, and the Clinical Guidelines maintained by the British Columbia Cancer Agency (Canada) and the British Dental Association (UK) respectively. Conclusions: There are web-based, HCP-addressed, resources on screening for oral cancer housing heterogeneous information both in quality and contents. The use of specific evaluation tools permits the selection of reliable websites on this topic with a potential to improve the existing educational gaps among HCPs. Key words:Oral cancer, early diagnosis, screening, secondary prevention, internet, teaching resources, continuous education. PMID:25475775

  7. Web-based tools from AHRQ's National Resource Center.

    Science.gov (United States)

    Cusack, Caitlin M; Shah, Sapna

    2008-11-06

    The Agency for Healthcare Research and Quality (AHRQ) has made an investment of over $216 million in research around health information technology (health IT). As part of their investment, AHRQ has developed the National Resource Center for Health IT (NRC) which includes a public domain Web site. New content for the web site, such as white papers, toolkits, lessons from the health IT portfolio and web-based tools, is developed as needs are identified. Among the tools developed by the NRC are the Compendium of Surveys and the Clinical Decision Support (CDS) Resources. The Compendium of Surveys is a searchable repository of health IT evaluation surveys made available for public use. The CDS Resources contains content which may be used to develop clinical decision support tools, such as rules, reminders and templates. This live demonstration will show the access, use, and content of both these freely available web-based tools.

  8. Resources based factors of competitiveness of agricultural enterprises

    Directory of Open Access Journals (Sweden)

    Matyja Małgorzata

    2016-05-01

    Full Text Available Among many different definitions of competitiveness it is difficult to pinpoint the most appropriate one. In the paper it was defined as the ability to be profitable by effective use of available resources. The profitability ratios (ROS, ROA, ROE and value index were proposed as measures of competitiveness and resources were indicated as one of the group of factors that has an impact on it. Precisely, the purpose of the paper was to examine the relationship between selected resourced based factors and competitiveness of agricultural enterprises. The study was done with the use of correlation analysis on the basis of statistical data on selected Polish companies operating in agriculture. The main finding was that the analyzed resources (the level of labour, size and quality of agricultural land and size of assets were weakly correlated with competitiveness. This observation means that other factors have stronger impact on agricultural company’s competitiveness. They can refer to intangible resources (such as relational capital, know-how, managerial competencies, technological resources etc. and external conditions (such as climate, legal issues of agricultural enterprises.

  9. Recurrent fuzzy ranking methods

    Science.gov (United States)

    Hajjari, Tayebeh

    2012-11-01

    With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

  10. Optimal Allocation of Water Resources Based on Water Supply Security

    Directory of Open Access Journals (Sweden)

    Jianhua Wang

    2016-06-01

    Full Text Available Under the combined impacts of climate change and human activities, a series of water issues, such as water shortages, have arisen all over the world. According to current studies in Science and Nature, water security has become a frontier critical topic. Water supply security (WSS, which is the state of water resources and their capacity and their capacity to meet the demand of water users by water supply systems, is an important part of water security. Currently, WSS is affected by the amount of water resources, water supply projects, water quality and water management. Water shortages have also led to water supply insecurity. WSS is now evaluated based on the balance of the supply and demand under a single water resources condition without considering the dynamics of the varying conditions of water resources each year. This paper developed an optimal allocation model for water resources that can realize the optimal allocation of regional water resources and comprehensively evaluate WSS. The objective of this model is to minimize the duration of water shortages in the long term, as characterized by the Water Supply Security Index (WSSI, which is the assessment value of WSS, a larger WSSI value indicates better results. In addition, the simulation results of the model can determine the change process and dynamic evolution of the WSS. Quanzhou, a city in China with serious water shortage problems, was selected as a case study. The allocation results of the current year and target year of planning demonstrated that the level of regional comprehensive WSS was significantly influenced by the capacity of water supply projects and the conditions of the natural water resources. The varying conditions of the water resources allocation results in the same year demonstrated that the allocation results and WSSI were significantly affected by reductions in precipitation, decreases in the water yield coefficient, and changes in the underlying surface.

  11. The Resource-Based View and Value: The Customer-Based View of the Firm

    Science.gov (United States)

    Clulow, Val; Barry, Carol; Gerstman, Julie

    2007-01-01

    Purpose: The resource-based view (RBV) explores the role of key resources, identified as intangible assets and capabilities, in creating competitive advantage and superior performance. To a great extent the conceptual analysis and empirical research within the RBV has focused on the firm's perspective of key resources and the value to the firm of…

  12. Error analysis of stochastic gradient descent ranking.

    Science.gov (United States)

    Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

    2013-06-01

    Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

  13. An Analytic Hierarchy Process-based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System.

    Science.gov (United States)

    Alharthi, Hana; Sultana, Nahid; Al-Amoudi, Amjaad; Basudan, Afrah

    2015-01-01

    Pharmacy barcode scanning is used to reduce errors during the medication dispensing process. However, this technology has rarely been used in hospital pharmacies in Saudi Arabia. This article describes the barriers to successful implementation of a barcode scanning system in Saudi Arabia. A literature review was conducted to identify the relevant critical success factors (CSFs) for a successful dispensing barcode system implementation. Twenty-eight pharmacists from a local hospital in Saudi Arabia were interviewed to obtain their perception of these CSFs. In this study, planning (process flow issues and training requirements), resistance (fear of change, communication issues, and negative perceptions about technology), and technology (software, hardware, and vendor support) were identified as the main barriers. The analytic hierarchy process (AHP), one of the most widely used tools for decision making in the presence of multiple criteria, was used to compare and rank these identified CSFs. The results of this study suggest that resistance barriers have a greater impact than planning and technology barriers. In particular, fear of change is the most critical factor, and training is the least critical factor.

  14. A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking

    Directory of Open Access Journals (Sweden)

    pijitra jomsri

    2015-11-01

    Full Text Available Social bookmarking and publication sharing systems are essential tools for web resource discovery. The performance and capabilities of search results from research paper bookmarking system are vital. Many researchers use social bookmarking for searching papers related to their topics of interest. This paper proposes a combination of similarity based indexing “tag title and abstract” and static ranking to improve search results. In this particular study, the year of the published paper and type of research paper publication are combined with similarity ranking called (HybridRank. Different weighting scores are employed. The retrieval performance of these weighted combination rankings are evaluated using mean values of NDCG. The results suggest that HybridRank and similarity rank with weight 75:25 has the highest NDCG scores. From the preliminary result of experiment, the combination ranking technique provide more relevant research paper search results. Furthermore the chosen heuristic ranking can improve the efficiency of research paper searching on social bookmarking websites.

  15. Resource management in Diffserv measurement-based admission control PHR

    NARCIS (Netherlands)

    Westberg, L.; Heijenk, Geert; Karagiannis, Georgios; Oosthoek, S.; Partain, D.; Rexhepi, Vlora; Szabo, R.; Wallentin, P.; El Allali, H.

    2002-01-01

    The purpose of this draft is to present the Resource Management in Diffserv (RMD) Measurement-Based Admission Control (RIMA) Per Hop Reservation (PHR) protocol. The RIMA PHR protocol is used on a per-hop basis in a Differentiated Services (Diffserv) domain and extends the Diffserv Per Hop Behavior

  16. Scenario-based approach for flexible resource loading under uncertainty

    NARCIS (Netherlands)

    Wullink, G.; Gademann, A.J.R.M.; Hans, E.W.; Harten, van A.

    2004-01-01

    Order acceptance decisions in manufacture-to-order environments are often made based on incomplete or uncertain information. To quote reliable due dates in order processing, manage resource capacity adequately and take into account uncertainty, the paper presents and analyses models and tools for

  17. Incorporating Campus-Based Cultural Resources into Humanities Courses

    Science.gov (United States)

    Traver, Amy E.; Nedd, Rolecia

    2018-01-01

    In this article, the authors reviewed one effort to deepen students' connections to the humanities through the use of campus-based cultural resources at Queensborough Community College (QCC) of the City University of New York (CUNY), a minority-serving institution in one of the most diverse counties in the United States. Focusing specifically on…

  18. Assessing the contribution of Community-Based Natural Resources ...

    African Journals Online (AJOL)

    This study assessed Community-Based Natural Resources Management Programme (CBNRMP) for environmental sustainability in Ondo State, Nigeria. Data were gathered through a structured interview schedule from 120 rural dwellers participating in CBNRMP. Data collected were described with descriptive statistical ...

  19. Development of Computer-Based Resources for Textile Education.

    Science.gov (United States)

    Hopkins, Teresa; Thomas, Andrew; Bailey, Mike

    1998-01-01

    Describes the production of computer-based resources for students of textiles and engineering in the United Kingdom. Highlights include funding by the Teaching and Learning Technology Programme (TLTP), courseware author/subject expert interaction, usage test and evaluation, authoring software, graphics, computer-aided design simulation, self-test…

  20. Community-based Natural Resource Management of the Jozani ...

    African Journals Online (AJOL)

    Community-based Natural Resource Management (CBNRM) is an approach that has generally .... rules in use across a broad range of CPR user- communities .... identified these social clusters and vocational groupings as ..... satisfied with the agreement and the villagers .... protection measures for the red colobus monkey ...

  1. Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics.

    Science.gov (United States)

    Dao, Tien Tuan; Hoang, Tuan Nha; Ta, Xuan Hien; Tho, Marie Christine Ho Ba

    2013-02-01

    Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Resource-based optimization of electric power production (in Iran)

    International Nuclear Information System (INIS)

    Sadeghzadeh, Mohammad

    1999-01-01

    This paper is about electric power production optimization and chiefly discusses on the types of resources available in Iran. The modeling has been based on the marginal cost of different energy resources and types of technologies used. the computed costs are the basic standards for optimization of the production system of energy. the costs associated with environmental pollution and also pollution control are considered. the present paper also studied gas fossil fuel, hydro, nuclear, renewable and co-generation of heat and power. The results are discussed and reported at the last of the paper

  3. Developing a Theory-Based Simulation Educator Resource.

    Science.gov (United States)

    Thomas, Christine M; Sievers, Lisa D; Kellgren, Molly; Manning, Sara J; Rojas, Deborah E; Gamblian, Vivian C

    2015-01-01

    The NLN Leadership Development Program for Simulation Educators 2014 faculty development group identified a lack of a common language/terminology to outline the progression of expertise of simulation educators. The group analyzed Benner's novice-to-expert model and applied its levels of experience to simulation educator growth. It established common operational categories of faculty development and used them to organize resources that support progression toward expertise. The resulting theory-based Simulator Educator Toolkit outlines levels of ability and provides quality resources to meet the diverse needs of simulation educators and team members.

  4. Ranking as parameter estimation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Guy, Tatiana Valentine

    2009-01-01

    Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

  5. MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

    International Nuclear Information System (INIS)

    Xu, Q; Liu, H; Xing, L; Yu, H; Wang, G

    2016-01-01

    Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channel and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral

  6. MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Q [Xi’an Jiaotong University, Xi’an (China); Stanford University School of Medicine, Stanford, CA (United States); Liu, H; Xing, L [Stanford University School of Medicine, Stanford, CA (United States); Yu, H [University of Massachusetts Lowell, Lowell, MA (United States); Wang, G [Rensselaer Polytechnic Instute., Troy, NY (United States)

    2016-06-15

    Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channel and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral

  7. Classification of rank 2 cluster varieties

    DEFF Research Database (Denmark)

    Mandel, Travis

    We classify rank 2 cluster varieties (those whose corresponding skew-form has rank 2) according to the deformation type of a generic fiber U of their X-spaces, as defined by Fock and Goncharov. Our approach is based on the work of Gross, Hacking, and Keel for cluster varieties and log Calabi...

  8. Dynamic collective entity representations for entity ranking

    NARCIS (Netherlands)

    Graus, D.; Tsagkias, M.; Weerkamp, W.; Meij, E.; de Rijke, M.

    2016-01-01

    Entity ranking, i.e., successfully positioning a relevant entity at the top of the ranking for a given query, is inherently difficult due to the potential mismatch between the entity's description in a knowledge base, and the way people refer to the entity when searching for it. To counter this

  9. PageRank versatility analysis of multilayer modality-based network for exploring the evolution of oil-water slug flow.

    Science.gov (United States)

    Gao, Zhong-Ke; Dang, Wei-Dong; Li, Shan; Yang, Yu-Xuan; Wang, Hong-Tao; Sheng, Jing-Ran; Wang, Xiao-Fan

    2017-07-14

    Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks. Our analysis allows characterizing the complicated evolution of oil-water slug flow, from the opening formation of oil slugs, to the succedent inter-collision and coalescence among oil slugs, and then to the dispersed oil bubbles. These properties render our developed method particularly powerful for mining the essential flow features from the multilayer sensor measurements.

  10. Characterizing contract-based multiagent resource allocation in networks.

    Science.gov (United States)

    An, Bo; Lesser, Victor

    2010-06-01

    We consider a multiagent resource allocation problem where individual users intend to route traffic by requesting the help of entities across a network, and a cost is incurred at each network node that depends on the amount of traffic to be routed. We propose to study contract-based network resource allocation. In our model, users and nodes in the network make contracts before nodes route traffic for the users. The problem is an interesting self-interested negotiation problem because it requires the complete assembly of a set of distinct resources, and there are multiple combinations of distinct resources that could satisfy the goal of negotiation. First, we characterize the network allocation problem and show that finding optimal allocations is NP-complete and is inapproximable. We take both Nash equilibrium and pairwise Nash equilibrium as the solution concepts to characterize the equilibrium allocations. We find that, for any resource allocation game, Nash equilibrium and pairwise Nash equilibrium always exist. In addition, socially optimal allocations are always supported by Nash equilibrium and pairwise Nash equilibrium. We introduce best-response dynamics in which each agent takes a myopic best-response strategy and interacts with each other to dynamically form contracts. We analyze the convergence of the dynamics in some special cases. We also experimentally study the convergence rate of the dynamics and how efficient the evolved allocation is as compared with the optimal allocation in a variety of environments.

  11. Resource-based learning strategies: implications for students and institutions

    Directory of Open Access Journals (Sweden)

    Malcolm Ryan

    1996-12-01

    Full Text Available In its strategic plan, the University of Greenwich envisages a significant shift to resource-based learning (RBL. Enterprise in Higher Education (EHE has funded five pilot RBL projects during the past year, including one in introductory economics. The project was managed by three lecturers in the School of Social Sciences, supported by an Academic Development Officer. Learning outcomes were completely revised, and a range of assessment strategies, including computer-based tests, was identified. A resources guide was produced which identified the materials and activities that would enable students to achieve the learning outcomes. A number of innovations were adopted, including: • computer-based curriculum delivery, assessment, and student evaluation of the course; • an open approach to assessment; • abolishing lectures in favour of a diverse range of teaching and learning activities.

  12. Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon's entropy

    International Nuclear Information System (INIS)

    Bian Yiwen; Yang Feng

    2010-01-01

    Data envelopment analysis (DEA) has been widely used in energy efficiency and environment efficiency analysis in recent years. Based on the existing environment DEA technology, this paper presents several DEA models for estimating the aggregated efficiency of resource and environment. These models can evaluate DMUs' energy efficiencies and environment efficiencies simultaneously. However, efficiency ranking results obtained from these models are not the same, and each model can provide some valuable information of DMUs' efficiencies, which we could not ignore. Under this situation, it may be hard for us to choose a specific model in practice. To address this kind of performance evaluation problem, the current paper extends Shannon-DEA procedure to establish a comprehensive efficiency measure for appraising DMUs' resource and environment efficiencies. In the proposed approach, the measure for evaluating a model's importance degree is provided, and the targets setting approach of inputs/outputs for DMU managers to improve DMUs' energy and environmental efficiencies is also discussed. We illustrate the proposed approach using real data set of 30 provinces in China.

  13. Multiplex PageRank.

    Science.gov (United States)

    Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

    2013-01-01

    Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  14. Multiplex PageRank.

    Directory of Open Access Journals (Sweden)

    Arda Halu

    Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  15. RankExplorer: Visualization of Ranking Changes in Large Time Series Data.

    Science.gov (United States)

    Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin

    2012-12-01

    For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.

  16. Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

    Science.gov (United States)

    Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

    2018-01-01

    The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. On the Effect of Group Structures on Ranking Strategies in Folksonomies

    Science.gov (United States)

    Abel, Fabian; Henze, Nicola; Krause, Daniel; Kriesell, Matthias

    Folksonomies have shown interesting potential for improving information discovery and exploration. Recent folksonomy systems explore the use of tag assignments, which combine Web resources with annotations (tags), and the users that have created the annotations. This article investigates on the effect of grouping resources in folksonomies, i.e. creating sets of resources, and using this additional structure for the tasks of search & ranking, and for tag recommendations. We propose several group-sensitive extensions of graph-based search and recommendation algorithms, and compare them with non group-sensitive versions. Our experiments show that the quality of search result ranking can be significantly improved by introducing and exploiting the grouping of resources (one-tailed t-Test, level of significance α=0.05). Furthermore, tag recommendations profit from the group context, and it is possible to make very good recommendations even for untagged resources- which currently known tag recommendation algorithms cannot fulfill.

  18. Comparing classical and quantum PageRanks

    Science.gov (United States)

    Loke, T.; Tang, J. W.; Rodriguez, J.; Small, M.; Wang, J. B.

    2017-01-01

    Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker's probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.

  19. Web-based resources for critical care education.

    Science.gov (United States)

    Kleinpell, Ruth; Ely, E Wesley; Williams, Ged; Liolios, Antonios; Ward, Nicholas; Tisherman, Samuel A

    2011-03-01

    To identify, catalog, and critically evaluate Web-based resources for critical care education. A multilevel search strategy was utilized. Literature searches were conducted (from 1996 to September 30, 2010) using OVID-MEDLINE, PubMed, and the Cumulative Index to Nursing and Allied Health Literature with the terms "Web-based learning," "computer-assisted instruction," "e-learning," "critical care," "tutorials," "continuing education," "virtual learning," and "Web-based education." The Web sites of relevant critical care organizations (American College of Chest Physicians, American Society of Anesthesiologists, American Thoracic Society, European Society of Intensive Care Medicine, Society of Critical Care Medicine, World Federation of Societies of Intensive and Critical Care Medicine, American Association of Critical Care Nurses, and World Federation of Critical Care Nurses) were reviewed for the availability of e-learning resources. Finally, Internet searches and e-mail queries to critical care medicine fellowship program directors and members of national and international acute/critical care listserves were conducted to 1) identify the use of and 2) review and critique Web-based resources for critical care education. To ensure credibility of Web site information, Web sites were reviewed by three independent reviewers on the basis of the criteria of authority, objectivity, authenticity, accuracy, timeliness, relevance, and efficiency in conjunction with suggested formats for evaluating Web sites in the medical literature. Literature searches using OVID-MEDLINE, PubMed, and the Cumulative Index to Nursing and Allied Health Literature resulted in >250 citations. Those pertinent to critical care provide examples of the integration of e-learning techniques, the development of specific resources, reports of the use of types of e-learning, including interactive tutorials, case studies, and simulation, and reports of student or learner satisfaction, among other general

  20. Statistically based uncertainty analysis for ranking of component importance in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor

    International Nuclear Information System (INIS)

    Wilson, G.E.

    1992-01-01

    The Analytic Hierarchy Process (AHP) has been used to help determine the importance of components and phenomena in thermal-hydraulic safety analyses of nuclear reactors. The AHP results are based, in part on expert opinion. Therefore, it is prudent to evaluate the uncertainty of the AHP ranks of importance. Prior applications have addressed uncertainty with experimental data comparisons and bounding sensitivity calculations. These methods work well when a sufficient experimental data base exists to justify the comparisons. However, in the case of limited or no experimental data the size of the uncertainty is normally made conservatively large. Accordingly, the author has taken another approach, that of performing a statistically based uncertainty analysis. The new work is based on prior evaluations of the importance of components and phenomena in the thermal-hydraulic safety analysis of the Advanced Neutron Source Reactor (ANSR), a new facility now in the design phase. The uncertainty during large break loss of coolant, and decay heat removal scenarios is estimated by assigning a probability distribution function (pdf) to the potential error in the initial expert estimates of pair-wise importance between the components. Using a Monte Carlo sampling technique, the error pdfs are propagated through the AHP software solutions to determine a pdf of uncertainty in the system wide importance of each component. To enhance the generality of the results, study of one other problem having different number of elements is reported, as are the effects of a larger assumed pdf error in the expert ranks. Validation of the Monte Carlo sample size and repeatability are also documented

  1. Vision-based coaching: optimizing resources for leader development

    Science.gov (United States)

    Passarelli, Angela M.

    2015-01-01

    Leaders develop in the direction of their dreams, not in the direction of their deficits. Yet many coaching interactions intended to promote a leader’s development fail to leverage the benefits of the individual’s personal vision. Drawing on intentional change theory, this article postulates that coaching interactions that emphasize a leader’s personal vision (future aspirations and core identity) evoke a psychophysiological state characterized by positive emotions, cognitive openness, and optimal neurobiological functioning for complex goal pursuit. Vision-based coaching, via this psychophysiological state, generates a host of relational and motivational resources critical to the developmental process. These resources include: formation of a positive coaching relationship, expansion of the leader’s identity, increased vitality, activation of learning goals, and a promotion–orientation. Organizational outcomes as well as limitations to vision-based coaching are discussed. PMID:25926803

  2. Vision-based coaching: Optimizing resources for leader development

    Directory of Open Access Journals (Sweden)

    Angela M. Passarelli

    2015-04-01

    Full Text Available Leaders develop in the direction of their dreams, not in the direction of their deficits. Yet many coaching interactions intended to promote a leader’s development fail to leverage the developmental benefits of the individual’s personal vision. Drawing on Intentional Change Theory, this article postulates that coaching interactions that emphasize a leader’s personal vision (future aspirations and core identity evoke a psychophysiological state characterized by positive emotions, cognitive openness, and optimal neurobiological functioning for complex goal pursuit. Vision-based coaching, via this psychophysiological state, generates a host of relational and motivational resources critical to the developmental process. These resources include: formation of a positive coaching relationship, expansion of the leader’s identity, increased vitality, activation of learning goals, and a promotion-orientation. Organizational outcomes as well as limitations to vision-based coaching are discussed.

  3. Satellite based wind resource assessment over the South China Sea

    DEFF Research Database (Denmark)

    Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay

    2014-01-01

    variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping...... years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile...... from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical...

  4. Human resource recommendation algorithm based on ensemble learning and Spark

    Science.gov (United States)

    Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

    2017-08-01

    Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

  5. Can we rank scholarly book publishers? A bibliometric experiment with the field of history

    NARCIS (Netherlands)

    Zuccala, A.; Guns, R.; Cornacchia, R.; Bod, R.

    2015-01-01

    This is a publisher ranking study based on a citation data grant from Elsevier, specifically, book titles cited in Scopus history journals (2007-2011) and matching metadata from WorldCat® (i.e., OCLC numbers, ISBN codes, publisher records, and library holding counts). Using both resources, we have

  6. Managing Knowledge-Based Resource Capabilities Under Uncertainty

    OpenAIRE

    Janice E. Carrillo; Cheryl Gaimon

    2004-01-01

    A firm's ability to manage its knowledge-based resource capabilities has become increasingly important as a result of performance threats triggered by technology change and intense competition. At the manufacturing plant level, we focus on three repositories of knowledge that drive performance. First, the physical production or information systems represent knowledge embedded in the plant's technical systems. Second, the plant's workforce has knowledge, including diverse scientific informatio...

  7. Entrepreneurship, Subjectivism, and the Resource-based View

    DEFF Research Database (Denmark)

    Foss, Nicolai Juul; Klein, Peter G.; Kor, Yasemin Y.

    This paper maintains that the consistent application of subjectivism helps to reconcile contemporary entrepreneurship theory with strategic management research in general, and the resource−based view in particular. The paper synthesizes theoretical insights from Austrian economics and Penrose......'s (1959) resources approach, arguing that entrepreneurship is inherently subjective and firm specific. This new synthesis describes how entrepreneurship is manifested in teams, and is driven by both heterogeneity of managerial mental models and shared team experiences....

  8. Dynamic Matrix Rank

    DEFF Research Database (Denmark)

    Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

    2009-01-01

    We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

  9. Awareness-based game-theoretic space resource management

    Science.gov (United States)

    Chen, Genshe; Chen, Huimin; Pham, Khanh; Blasch, Erik; Cruz, Jose B., Jr.

    2009-05-01

    Over recent decades, the space environment becomes more complex with a significant increase in space debris and a greater density of spacecraft, which poses great difficulties to efficient and reliable space operations. In this paper we present a Hierarchical Sensor Management (HSM) method to space operations by (a) accommodating awareness modeling and updating and (b) collaborative search and tracking space objects. The basic approach is described as follows. Firstly, partition the relevant region of interest into district cells. Second, initialize and model the dynamics of each cell with awareness and object covariance according to prior information. Secondly, explicitly assign sensing resources to objects with user specified requirements. Note that when an object has intelligent response to the sensing event, the sensor assigned to observe an intelligent object may switch from time-to-time between a strong, active signal mode and a passive mode to maximize the total amount of information to be obtained over a multi-step time horizon and avoid risks. Thirdly, if all explicitly specified requirements are satisfied and there are still more sensing resources available, we assign the additional sensing resources to objects without explicitly specified requirements via an information based approach. Finally, sensor scheduling is applied to each sensor-object or sensor-cell pair according to the object type. We demonstrate our method with realistic space resources management scenario using NASA's General Mission Analysis Tool (GMAT) for space object search and track with multiple space borne observers.

  10. Proceedings of the sixteenth biennial low-rank fuels symposium

    International Nuclear Information System (INIS)

    1991-01-01

    Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium

  11. Proceedings of the sixteenth biennial low-rank fuels symposium

    Energy Technology Data Exchange (ETDEWEB)

    1991-01-01

    Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium.

  12. Piloting an email-based resource package for job seekers with multiple sclerosis.

    Science.gov (United States)

    Dorstyn, Diana; Roberts, Rachel; Murphy, Gregory; Kneebone, Ian; Migliorini, Christine; Craig, Ashley; Hutchinson, Claire; Field, Deborah

    2017-05-01

    Media-based rehabilitation provides a powerful opportunity to examine vocational behaviors in the disability sector. However, this research is preliminary at best. This paper reports pilot data. Eighteen adults with multiple sclerosis (MS) accessed an email-delivered, resource-based package, Work and MS. Pre- and post-access vocational self-efficacy and identity (Job-Procurement Self Efficacy Scale, My Vocational Situation Scale- primary outcomes), life orientation and depressed mood (Life Orientation Test - revised and Patient Health Questionnaire-9 - secondary outcomes) were assessed. Pre- and post-change scores were examined with Wilcoxon signed ranks tests and Hedges g effect sizes with associated 95% confidence intervals. Reliable change analyses were additionally calculated to determine the clinical significance of individual change scores. Significant and positive effects were reported for vocational self-efficacy, identity, and optimism. Reliable change scores in one or more of these key outcomes were reported by 30% of the sample. Satisfaction with the content and delivery of the email-based intervention was also noted. Preliminary evidence suggests that Work and MS can help to promote vocational goals, interests and strengths among job seekers with a disability by providing a set of tools, information and linkages relating to vocational pursuits and career development. Replication with a randomized control design is indicated. Implications for Rehabilitation Research indicates a high unemployment rate among working-age adults with MS. A combination of disease-specific, psychological, programmatic and societal variables contribute to employment instability in this group. This pilot study demonstrates that an e-mail-based resource package, Work and MS, provides an innovative and feasible option for promoting consumer engagement with vocational services and, potentially, improving vocational outcomes. Work and MS has potential applicability to other

  13. Ranking the criteria for sustainability of community-based rural homestay programmes from the perspective of the operators

    Science.gov (United States)

    Ramli, Rohaini; Kasim, Maznah Mat; Ramli, Razamin; Kayat, Kalsom; Razak, Rafidah Abd

    2015-12-01

    Homestay is one of the government's products that promote the cultural tourism of country around the world. Homestay in Malaysia is not only thriving, but also its operation is moving gradually toward development of economic growth. Many homestays have been built throughout the country and this will give tourists an opportunity to enjoy the different and interesting environment in Malaysia. However, most of them receive less support from tourists and only certain numbers of homestays have operated consistently. This paper examines eleven sustainability criteria for homestay programme in Malaysia covering environmental, economic and sociocultural dimensions. The required data were collected through a survey of 246 homestay operators using a structured questionnaire. Data obtained was analyzed by utilizing percentage and arithmetic average. The findings revealed that the three most important criteria for homestay to remain sustained in this business area are ability and capacity, leadership and conservation of community resources. In order to improve the business performance of homestays in this country, homestay operators should focus on improving their ability and capacity and focus on enhancing their leadership skills.

  14. A Relative Ranking Approach for Nano-Enabled Applications to Improve Risk-Based Decision Making: A Case Study of Army Materiel

    Science.gov (United States)

    2014-12-24

    accidental expo- sures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank highest relative to...that inhalation from accidental exposures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank... copper (Cu), and titanium (Ti) flakes used in smokes and obscurants ranked the highest on the risk scale for sce- narios primarily involving accidental

  15. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  16. General active space commutator-based coupled cluster theory of general excitation rank for electronically excited states: implementation and application to ScH.

    Science.gov (United States)

    Hubert, Mickaël; Olsen, Jeppe; Loras, Jessica; Fleig, Timo

    2013-11-21

    We present a new implementation of general excitation rank coupled cluster theory for electronically excited states based on the single-reference multi-reference formalism. The method may include active-space selected and/or general higher excitations by means of the general active space concept. It may employ molecular integrals over the four-component Lévy-Leblond Hamiltonian or the relativistic spin-orbit-free four-component Hamiltonian of Dyall. In an initial application to ground- and excited states of the scandium monohydride molecule we report spectroscopic constants using basis sets of up to quadruple-zeta quality and up to full iterative triple excitations in the cluster operators. Effects due to spin-orbit interaction are evaluated using two-component multi-reference configuration interaction for assessing the accuracy of the coupled cluster results.

  17. Geothermal resources in Oregon: site data base and development status

    Energy Technology Data Exchange (ETDEWEB)

    Justus, D.L.

    1979-04-01

    An inventory of resources based on available information is presented. Potential for utilization and the legal and institutional environment in which development is likely to occur were also considered. Sites selected for this investigation include the 13 identified KGRA's, one PGRA which was chosen because of substantial local interest expressed in favor of development, and one major geologic fault zone which shows indications of high potential. Each chapter represents a planning region and is introduced by a regional overview of the physical setting followed by a narrative summary statement of the specific resource location and characteristics, existing utilization and potential end-uses for future development. Detailed site information in the form of data sheets follows each narrative. (MHR)

  18. Towards minimal resources of measurement-based quantum computation

    International Nuclear Information System (INIS)

    Perdrix, Simon

    2007-01-01

    We improve the upper bound on the minimal resources required for measurement-only quantum computation (M A Nielsen 2003 Phys. Rev. A 308 96-100; D W Leung 2004 Int. J. Quantum Inform. 2 33; S Perdrix 2005 Int. J. Quantum Inform. 3 219-23). Minimizing the resources required for this model is a key issue for experimental realization of a quantum computer based on projective measurements. This new upper bound also allows one to reply in the negative to the open question presented by Perdrix (2004 Proc. Quantum Communication Measurement and Computing) about the existence of a trade-off between observable and ancillary qubits in measurement-only QC

  19. Managing Human Resource based Intellectual Capital in a Global setting

    DEFF Research Database (Denmark)

    Gretzinger, Susanne; Lemke, Sarah; Matiaske, Wenzel

    2014-01-01

    From a strategic management perspective human capital and the embedded knowledge can be viewed as intellectual capital and became inevitably important for companies in general as well as for multinationals. While national companies just have to (re-)combine resources within a homogeneous...... if culturally differentiated incentive systems are necessary for optimised retention management? In the empirical part of this study it was made us of data from 32 countries. The research results reveal a moderating impact of cultural dimensions and therefore a cultural dependency for the effectiveness...... of incentives on retention management and therewith implicates that retention management is significant for the process of developing and fostering a MNCs intellectual capital. To improve their human-resource based intellectual capital MNCs have to adapt their initiatives to the cultural background...

  20. Location-based resource allocation for OFDMA cognitive radio systems

    KAUST Repository

    Nam, Haewoon

    2010-01-01

    In cognitive radio systems, in order for the secondary users to opportunistically share the spectrum without interfering the primary users, an accurate spectrum measurement and a precise estimation of the interference at the primary users are necessary but are challenging tasks. Since it is impractical in cognitive radio systems to assume that the channel state information of the interference link is available at the cognitive transmitter, the interference at the primary users is hard to be estimated accurately. This paper introduces a resource allocation algorithm for OFDMA-based cognitive radio systems, which utilizes location information of the primary and secondary users instead of the channel state information of the interference link. Simulation results show that it is indeed effective to incorporate location information into resource allocation so that a near-optimal capacity is achieved.

  1. Rankings of Economics Faculties and Representation on Editorial Boards of Top Journals.

    Science.gov (United States)

    Gibbons, Jean D.; Fish, Mary

    1991-01-01

    Presents rankings of U.S., university, economics departments. Explains the rankings are based upon representation of the departments on the editorial boards of leading economics journals. Reports that results are similar to rankings based upon other criteria. (DK)

  2. College Rankings. ERIC Digest.

    Science.gov (United States)

    Holub, Tamara

    The popularity of college ranking surveys published by "U.S. News and World Report" and other magazines is indisputable, but the methodologies used to measure the quality of higher education institutions have come under fire by scholars and college officials. Criticisms have focused on methodological flaws, such as failure to consider…

  3. OutRank

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

    2008-01-01

    Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

  4. A Ranking Approach to Genomic Selection.

    Science.gov (United States)

    Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

    2015-01-01

    Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

  5. Identifying city PV roof resource based on Gabor filter

    Science.gov (United States)

    Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

    2017-06-01

    To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

  6. Improving Ranking Using Quantum Probability

    OpenAIRE

    Melucci, Massimo

    2011-01-01

    The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

  7. Risk based maintenance: Resource requirements and organizational challenges

    International Nuclear Information System (INIS)

    Weerakkody, S.D.

    2000-01-01

    10CFR50.65 'Requirements for Monitoring the Effectiveness of Maintenance at Nuclear Power Plants' required licensees to monitor the performance or condition of structures, systems, or components (SSCs) against licensee established goals, in a manner sufficient to provide reasonable assurance that such SSCs are capable of fulfilling their intended functions. The goals were required to be commensurate with safety significance and operating experience. Northeast Utilities relied upon PRAs to implement 10CFR50.65, which is also referred to as the 'Maintenance Rule'. The Maintenance Rule changed some aspects of maintenance of structures, systems, and components (SSC) at nuclear power plants. One objective of the rule was to focus the maintenance resources based on risk significance of components. This paper will discuss the organizational challenges and resource requirements associated with implementation of the Maintenance Rule at nuclear facilities that are supported by the Northeast Utilities Services Company (NUSCo). The paper will discuss (a) how these challenges were addressed, (b) the resources required for ongoing efforts to support the Maintenance Rule, and (c) several key safety benefits derived from the implementation of the Maintenance Rule. (author)

  8. A tilting approach to ranking influence

    KAUST Repository

    Genton, Marc G.

    2014-12-01

    We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

  9. Resource Discovery in Activity-Based Sensor Networks

    DEFF Research Database (Denmark)

    Bucur, Doina; Bardram, Jakob

    This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networ....... ABSN enhances the generic Extended Zone Routing Protocol with logical sensor grouping and greatly lowers network overhead during the process of discovery, while keeping discovery latency close to optimal.......This paper proposes a service discovery protocol for sensor networks that is specifically tailored for use in humancentered pervasive environments. It uses the high-level concept of computational activities (as logical bundles of data and resources) to give sensors in Activity-Based Sensor Networks...... (ABSNs) knowledge about their usage even at the network layer. ABSN redesigns classical network-level service discovery protocols to include and use this logical structuring of the network for a more practically applicable service discovery scheme. Noting that in practical settings activity-based sensor...

  10. Low rank magnetic resonance fingerprinting.

    Science.gov (United States)

    Mazor, Gal; Weizman, Lior; Tal, Assaf; Eldar, Yonina C

    2016-08-01

    Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.

  11. Parallel Harmony Search Based Distributed Energy Resource Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Ceylan, Oguzhan [ORNL; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

    2015-01-01

    This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.

  12. Renewable resources-based approach to biantennary glycolipids.

    Science.gov (United States)

    Tabandeh, Mojtaba; Salman, Abbas Abdulameer; Goh, Ean Wai; Heidelberg, Thorsten; Hussen, Rusnah Syahila Duali

    2018-01-31

    A new synthesis approach towards biantennary lipids of Guerbet glycoside type was developed based on oleic acid as sustainable resource. Functionalization of the double bond provided access to primary alcohols with α-branched C 19 -skeleton. Formulation studies with corresponding lactosides indicated formation of vesicles with high assembly stability. A relatively narrow bimodal size distribution of the latter, which turns into a narrow unimodal distribution of small vesicles upon addition of an ionic cosurfactant, suggests potential for a vesicular drug delivery system. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Morpheme matching based text tokenization for a scarce resourced language.

    Science.gov (United States)

    Rehman, Zobia; Anwar, Waqas; Bajwa, Usama Ijaz; Xuan, Wang; Chaoying, Zhou

    2013-01-01

    Text tokenization is a fundamental pre-processing step for almost all the information processing applications. This task is nontrivial for the scarce resourced languages such as Urdu, as there is inconsistent use of space between words. In this paper a morpheme matching based approach has been proposed for Urdu text tokenization, along with some other algorithms to solve the additional issues of boundary detection of compound words, affixation, reduplication, names and abbreviations. This study resulted into 97.28% precision, 93.71% recall, and 95.46% F1-measure; while tokenizing a corpus of 57000 words by using a morpheme list with 6400 entries.

  14. AN OVERVIEW OF SEARCHING AND DISCOVERING WEB BASED INFORMATION RESOURCES

    Directory of Open Access Journals (Sweden)

    Cezar VASILESCU

    2010-01-01

    Full Text Available The Internet becomes for most of us a daily used instrument, for professional or personal reasons. We even do not remember the times when a computer and a broadband connection were luxury items. More and more people are relying on the complicated web network to find the needed information.This paper presents an overview of Internet search related issues, upon search engines and describes the parties and the basic mechanism that is embedded in a search for web based information resources. Also presents ways to increase the efficiency of web searches, through a better understanding of what search engines ignore at websites content.

  15. A Difference-Index Based Ranking Bilinear Programming Approach to Solving Bimatrix Games with Payoffs of Trapezoidal Intuitionistic Fuzzy Numbers

    Directory of Open Access Journals (Sweden)

    Deng-Feng Li

    2013-01-01

    Full Text Available The aim of this paper is to develop a bilinear programming method for solving bimatrix games in which the payoffs are expressed with trapezoidal intuitionistic fuzzy numbers (TrIFNs, which are called TrIFN bimatrix games for short. In this method, we define the value index and ambiguity index for a TrIFN and propose a new order relation of TrIFNs based on the difference index of value index to ambiguity index, which is proven to be a total order relation. Hereby, we introduce the concepts of solutions of TrIFN bimatrix games and parametric bimatrix games. It is proven that any TrIFN bimatrix game has at least one satisfying Nash equilibrium solution, which is equivalent to the Nash equilibrium solution of corresponding parametric bimatrix game. The latter can be obtained through solving the auxiliary parametric bilinear programming model. The method proposed in this paper is demonstrated with a real example of the commerce retailers’ strategy choice problem.

  16. A Universal Rank-Size Law

    Science.gov (United States)

    2016-01-01

    A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

  17. Understanding How Resources and Capabilities Affect Performance: Actively Applying the Resource-Based View in the Classroom

    Science.gov (United States)

    Sheehan, Norman T.

    2006-01-01

    The resource-based view is a strategic framework for understanding why some firms outperform others. Its importance is reflected in its wide inclusion in strategy texts as a tool for assessing a firm's internal strengths and weaknesses. This article outlines an experiential exercise that demonstrates how different bundles of resources and…

  18. Application of risk-based methodologies to prioritize safety resources

    International Nuclear Information System (INIS)

    Rahn, F.J.; Sursock, J.P.; Hosler, J.

    1993-01-01

    The Electric Power Research Institute (EPRI) started a program entitled risk-based prioritization in 1992. The purpose of this program is to provide generic technical support to the nuclear power industry relative to its recent initiatives in the area of operations and maintenance (O ampersand M) cost control using state-of-the-art risk methods. The approach uses probabilistic risk assessment (PRA), or similar techniques, to allocate resources commensurate with the risk posed by nuclear plant operations. Specifically, those items or events that have high risk significance would receive the most attention, while those with little risk content would command fewer resources. As quantified in a companion paper,close-quote the potential O ampersand M cost reduction inherent in this approach is very large. Furthermore, risk-based methods should also lead to safety improvements. This paper outlines the way that the EPRI technical work complements the technical, policy, and regulatory initiatives taken by others in the industry and provides an example of the approach as used to prioritize motor-operated valve (MOV) testing in response to US Nuclear Regulatory Commission (NRC) Generic Letter 89-10

  19. Distributed energy resources at naval base ventura county building 1512

    International Nuclear Information System (INIS)

    Bailey, Owen C.; Marnay, Chris

    2004-01-01

    This paper reports the findings of a preliminary assessment of the cost effectiveness of distributed energy resources at Naval Base Ventura County (NBVC) Building 1512. This study was conducted in response to the base's request for design assistance to the Federal Energy Management Program. Given the current tariff structure there are two main decisions facing NBVC: whether to install distributed energy resources (DER), or whether to continue the direct access energy supply contract. At the current effective rate, given assumptions about the performance and structure of building energy loads and available generating technology characteristics, the results of this study indicate that if the building installed a 600 kW DER system with absorption cooling and heat capabilities chosen by cost minimization, the energy cost savings would be about 14 percent, or $55,000 per year. However, under current conditions, this study also suggests that significant savings could be obtained if Building 1 512 changed from the direct access contract to a SCE TOU-8 (Southern California Edison time of use tariff number 8) rate without installing a DER system. At current SCE TOU-8 tariffs, the potential savings from installation of a DER system would be about 4 percent, or $15,000 per year

  20. Open Manufacturing: Impacts of Resource Based View and Servitisation

    DEFF Research Database (Denmark)

    Yang, Cheng; Johansen, John

    2010-01-01

    The environment of manufacturing has faced significant changes in the past decade. Meanwhile, the traditional focus of manufacturing strategy is also impacted by resource-based view and servitisation. Thus, no matter from a practical or theoretical perspective, it is time to rethink what kind...... of view we can have on manufacturing. In this paper, the literature is reviewed firstly to track the evolution of theories on manufacturing strategy and to investigate new views on manufacturing from a theoretical perspective. This is followed by three case studies, which are used to explore how...... manufacturing is used from a practical perspective. The usages of manufacturing are classified into three groups and their relationships are discussed further. Based on these findings and inspired by open source software (OSS) and open innovation, a new paradigm on manufacturing termed as “open manufacturing...

  1. Ranking Quality in Higher Education: Guiding or Misleading?

    Science.gov (United States)

    Bergseth, Brita; Petocz, Peter; Abrandt Dahlgren, Madeleine

    2014-01-01

    The study examines two different models of measuring, assessing and ranking quality in higher education. Do different systems of quality assessment lead to equivalent conclusions about the quality of education? This comparative study is based on the rankings of 24 Swedish higher education institutions. Two ranking actors have independently…

  2. PageRank as a method to rank biomedical literature by importance.

    Science.gov (United States)

    Yates, Elliot J; Dixon, Louise C

    2015-01-01

    Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

  3. Augmenting the Deliberative Method for Ranking Risks.

    Science.gov (United States)

    Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

    2016-01-01

    The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

  4. A Study of the Effects of Rank and Gender on Officers' Club Membership and Club Usage at U.S. Air Force Bases in the Continental United States

    National Research Council Canada - National Science Library

    Smith, C

    1999-01-01

    Scope and Method of Study: The purpose of this study was to examine relationships between both officer rank and officer gender and both club membership and member usage at Air Force officers' clubs in the Continental United States (CONUS...

  5. Artifact-based reflective interviews for identifying pragmatic epistemological resources

    Science.gov (United States)

    Shubert, Christopher Walden

    Physics Education Research studies the science of teaching and learning physics. The process of student learning is complex, and the factors that affect it are numerous. Describing students' understanding of physics knowledge and reasoning is the basis for much productive research; however, such research fails to account for certain types of student learning difficulties. In this dissertation, I explore one source of student difficulty: personal epistemology, students' ideas about knowledge and knowing. Epistemology traditionally answers three questions: What is knowledge? How is knowledge created? And, how do we know what we know? An individual's responses to these questions can affect learning in terms of how they approach tasks involving the construction and application of knowledge. The key issue addressed in this dissertation is the effect of methodological choices on the validity and reliability of claims concerning personal epistemology. My central concern is contextual validity, how what is said about one's epistemology is not identical to how one behaves epistemologically. In response to these issues, I present here a new methodology for research on student epistemology: video artifact-based reflective interview protocols. These protocols begin with video taping students in their natural classroom activities, and then asking the participants epistemological questions immediately after watching selected scenes from their activity, contextually anchoring them in their actual learning experience. The data from these interviews is viewed in the framework of Epistemological Resource Theory, a framework of small bits of knowledge whose coordination in a given context is used to describe personal epistemology. I claim that the privileged data from these interviews allows detailed epistemological resources to be identified, and that these resources can provide greater insight into how student epistemologies are applied in learning activities. This research

  6. Resource Allocation and Justice-based Arguments for Funding

    African Journals Online (AJOL)

    2018-03-01

    Mar 1, 2018 ... healthcare system that would ensure Nigerians, access to glaucoma treatment ...... proceeds from the sales of common patrimony of natural resources ..... Besides, it would plausibly optimize use of healthcare resources and.

  7. Robins Air Force Base integrated resource assessment. Volume 3, Resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, G.P.; Keller, J.M.; Stucky, D.J.; Wahlstrom, R.R.; Larson, L.L.

    1993-10-01

    The US Air Force Materiel Command (AFMC) has tasked the US Department of Energy (DOE) Federal Energy Management Program (FEMP), supported by the Pacific Northwest Laboratory (PNL), to identify, evaluate, and assist in acquiring all cost-effective energy projects at Robins Air Force Base (AFB). This is part of a model program that PNL is designing to support energy-use decisions in the federal sector. This report provides the results of the fossil fuel and electric energy resource opportunity (ERO) assessments performed by PNL at the AFMC Robins AFB facility located approximately 15 miles south of Macon, Georgia. It is a companion report to Volume 1, Executive Summary, and Volume 2, Baseline Detail. The results of the analyses of EROs are presented in 13 common energy end-use categories (e.g., boilers and furnaces, service hot water, and building lighting). A narrative-description of each ERO is provided, including information on the installed cost, energy and dollar savings; impacts on operation and maintenance (O&M); and, when applicable, a discussion of energy supply and demand, energy security, and environmental issues. A description of the evaluation methodologies and technical and cost assumptions is also provided for each ERO. Summary tables present the cost-effectiveness of energy end-use equipment before and after the implementation of each ERO and present the results of the life-cycle cost (LCC) analysis indicating the net present value (NPV) and savings to investment ratio (SIR) of each ERO.

  8. Patrick Air Force Base integrated resource assessment. Volume 3, Resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Sandusky, W.F.; Parker, S.A.; King, D.A.; Wahlstrom, R.R.; Elliott, D.B.; Shankle, S.A.

    1993-12-01

    The US Air Force has tasked the Pacific Northwest Laboratory (PNL) in support of the US Department of Energy Federal Energy Management Program to identify, evaluate, and assist in acquiring all cost effective energy projects at Patrick Air Force Base (AFB). This is part of a model program that PNL is designing to support energy-use decisions in the federal sector. This report provides the results of the fossil fuel and electric energy resource opportunity (ERO) assessments performed by PNL at Patrick AFB which is located south of Cocoa Beach, Florida. It is a companion report to Volume 1, Executive Summary, and Volume.2, Baseline Detail. The results of the analyses of EROs are presented in 11 common energy end-use categories. A narrative description of each ERO is provided, including information on the installed cost, energy and dollar savings, impacts on operations and maintenance, and, when applicable, a discussion of energy supply and demand, energy security, and environmental issues. A description of the evaluation methodologies and technical and cost assumptions is also provided for each ERO. Summary tables present the cost-effectiveness of energy end-use equipment before and after the implementation of each ERO and present the results of the life-cycle cost analysis indicating the net present value and value index of each ERO.

  9. Fourth-rank cosmology

    International Nuclear Information System (INIS)

    Marrakchi, A.E.L.; Tapia, V.

    1992-05-01

    Some cosmological implications of the recently proposed fourth-rank theory of gravitation are studied. The model exhibits the possibility of being free from the horizon and flatness problems at the price of introducing a negative pressure. The field equations we obtain are compatible with k obs =0 and Ω obs t clas approx. 10 20 t Planck approx. 10 -23 s. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. Hence, an interpretation of the negative pressure hypothesis is provided. (author). 8 refs

  10. Multidimensional ranking the design and development of U-Multirank

    CERN Document Server

    Ziegele, Frank

    2012-01-01

    During the last decades ranking has become one of the most controversial issues in higher education and research. It is widely recognized now that, although some of the current rankings can be severely criticized, they seem to be here to stay. In addition, rankings appear to have a great impact on decision-makers at all levels of higher education and research systems worldwide, including in universities. Rankings reflect a growing international competition among universities for talent and resources; at the same time they reinforce competition by their very results. Yet major concerns remain a

  11. Scalable Faceted Ranking in Tagging Systems

    Science.gov (United States)

    Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

    Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

  12. Evaluation of Web-Based Ostomy Patient Support Resources.

    Science.gov (United States)

    Pittman, Joyce; Nichols, Thom; Rawl, Susan M

    To evaluate currently available, no-cost, Web-based patient support resources designed for those who have recently undergone ostomy surgery. Descriptive, correlational study using telephone survey. The sample comprised 202 adults who had ostomy surgery within the previous 24 months in 1 of 5 hospitals within a large healthcare organization in the Midwestern United States. Two of the hospitals were academic teaching hospitals, and 3 were community hospitals. The study was divided into 2 phases: (1) gap analysis of 4 Web sites (labeled A-D) based on specific criteria; and (2) telephone survey of individuals with an ostomy. In phase 1, a comprehensive checklist based on best practice standards was developed to conduct the gap analysis. In phase 2, data were collected from 202 participants by trained interviewers via 1-time structured telephone interviews that required approximately 30 minutes to complete. Descriptive analyses were performed, along with correlational analysis of relationships among Web site usage, acceptability and satisfaction, demographic characteristics, and medical history. Gap analysis revealed that Web site D, managed by a patient advocacy group, received the highest total content score of 155/176 (88%) and the highest usability score of 31.7/35 (91%). Two hundred two participants completed the telephone interview, with 96 (48%) reporting that they used the Internet as a source of information. Sixty participants (30%) reported that friends or family member had searched the Internet for ostomy information on their behalf, and 148 (75%) indicated they were confident they could get information about ostomies on the Internet. Of the 90 participants (45%) who reported using the Internet to locate ostomy information, 73 (82%) found the information on the Web easy to understand, 28 (31%) reported being frustrated during their search for information, 24 (27%) indicated it took a lot of effort to get the information they needed, and 39 (43%) were

  13. University Rankings and Social Science

    Science.gov (United States)

    Marginson, Simon

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

  14. Customer Ranking Model for Project Businesses: A Case Study from the Automotive Industry

    Directory of Open Access Journals (Sweden)

    Bernd Markus Zunk

    2014-03-01

    Full Text Available For technology-orientated enterprises that operate project-based businesses, the goal-oriented allocation of scarce marketing resources has great potential to help consolidate their competitive position. An important precondition for goal-oriented management is the identification of the most valuable customers. This enables technology-orientated enterprises to segment markets in order to make tactical marketing decisions. This theorybased paper aims to develop and test a holistic customer ranking model. By deploying the five steps presented in this paper, customer relationship managers are better able to identify and to rank their customers in project-based businesses. A case study provides an example of the application of the method from the automotive industry in Austria. The experiences derived from this case study show that using a customer ranking framework is a crucial factor for enterprises in narrow technology markets to be successful and to achieve their corporate goals.

  15. On Row Rank Equal Column Rank

    Science.gov (United States)

    Khalili, Parviz

    2009-01-01

    We will prove a well-known theorem in Linear Algebra, that is, for any "m x n" matrix the dimension of row space and column space are the same. The proof is based on the subject of "elementary matrices" and "reduced row-echelon" form of a matrix.

  16. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

    Directory of Open Access Journals (Sweden)

    LI Lan-yin

    2017-04-01

    Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank,which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes,topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs,and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

  17. Method ranks competing projects by priorities, risk

    International Nuclear Information System (INIS)

    Moeckel, D.R.

    1993-01-01

    A practical, objective guide for ranking projects based on risk-based priorities has been developed by Sun Pipe Line Co. The deliberately simple system guides decisions on how to allocate scarce company resources because all managers employ the same criteria in weighing potential risks to the company versus benefits. Managers at all levels are continuously having to comply with an ever growing amount of legislative and regulatory requirements while at the same time trying to run their businesses effectively. The system primarily is designed for use as a compliance oversight and tracking process to document, categorize, and follow-up on work concerning various issues or projects. That is, the system consists of an electronic database which is updated periodically, and is used by various levels of management to monitor progress of health, safety, environmental and compliance-related projects. Criteria used in determining a risk factor and assigning a priority also have been adapted and found useful for evaluating other types of projects. The process enables management to better define potential risks and/or loss of benefits that are being accepted when a project is rejected from an immediate work plan or budget. In times of financial austerity, it is extremely important that the right decisions are made at the right time

  18. RankProdIt: A web-interactive Rank Products analysis tool

    Directory of Open Access Journals (Sweden)

    Laing Emma

    2010-08-01

    Full Text Available Abstract Background The first objective of a DNA microarray experiment is typically to generate a list of genes or probes that are found to be differentially expressed or represented (in the case of comparative genomic hybridizations and/or copy number variation between two conditions or strains. Rank Products analysis comprises a robust algorithm for deriving such lists from microarray experiments that comprise small numbers of replicates, for example, less than the number required for the commonly used t-test. Currently, users wishing to apply Rank Products analysis to their own microarray data sets have been restricted to the use of command line-based software which can limit its usage within the biological community. Findings Here we have developed a web interface to existing Rank Products analysis tools allowing users to quickly process their data in an intuitive and step-wise manner to obtain the respective Rank Product or Rank Sum, probability of false prediction and p-values in a downloadable file. Conclusions The online interactive Rank Products analysis tool RankProdIt, for analysis of any data set containing measurements for multiple replicated conditions, is available at: http://strep-microarray.sbs.surrey.ac.uk/RankProducts

  19. Griffiss Air Force Base integrated resource assessment. Volume 3, Electric resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, P.R.; Shankle, S.A.; Elliott, D.B.; Stucky, D.J.; Keller, J.M.; Wahlstrom, R.R.; Dagle, J.E.; Gu, A.Y.

    1993-09-01

    The US Air Force Air Combat Command (ACC) has tasked the US Department of Energy (DOE) Federal Energy Management Program (FEMP) to identify, evaluate, and assist in acquiring all cost-effective energy projects at Griffiss Air Force Base (AFB). FEMP, with support from the Pacific Northwest Laboratory (PNL), is designing this model program for federal customers served by the Niagara Mohawk Power Company. The program with Griffiss AFB will (1) identify and evaluate all cost-effective electric energy projects; (2) develop a schedule for project acquisition considering project type, size, timing, capital requirements, as well as energy and dollar savings; and (3) secure 100% of the financing required to implement electric energy efficiency projects from Niagara Mohawk and have them procure the necessary contractors to perform detailed audits and install the technologies. This report provides the results of the electric energy resource opportunity (ERO) assessments performed by PNL at one of Niagara Mohawk`s primary federal facilities, the ACC Griffiss AFB facility located near Rome, New York. The results of the analyses of EROs are presented in seven common energy end-use categories. A narrative description of each ERO provides information on the initial cost, energy and dollar savings; impacts on operations and maintenance (O&M); and, when applicable, a discussion of energy supply and demand, energy security, and environmental issues. The evaluation methodology and technical and cost assumptions are also described for each ERO. Summary tables present the operational performance of energy end-use equipment before and after the implementation of each ERO and the results of the life-cycle cost analysis indicating the net present value (NPV) and savings-to-investment ratio (SIR) of each ERO.

  20. Vandenberg Air Force Base integrated resource assessment. Volume 3, Resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Daellenbach, K.K.; Dagle, J.E.; Dittmer, A.L.; Elliott, D.B.; Halverson, M.A.; Hickman, B.J.; Parker, G.B.; Richman, E.E.; Shankle, S.A.

    1993-06-01

    The US Air Force Space Command (SPACECOM) has tasked the Pacific Northwest Laboratory (PNL), as the lead laboratory supporting the US Department of Energy (DOE) Federal Energy Management Program (FEMP), to identify, evaluate, and assist in acquiring all cost-effective energy projects at Vandenberg Air Force Base (VAFB). This is part of a model program that PNL is designing to support energy-use decisions in the federal sector. This report provides the results of the fossil fuel and electric energy resource opportunity (ERO) assessments performed by PNL at the SPACECOM VAFB facility located approximately 50 miles northwest of Santa Barbara, California. It is a companion report to Volume 1, Executive Summary, and Volume 2, Baseline Detail. The results of the analysis of EROs are presented in ten common energy end-use categories (e.g., boilers and furnaces, service hot water, and building lighting). In addition, a case study of process loads at Space Launch Complex-4 (SLC-4) is included. A narrative description of each ERO is provided, including information on the installed cost, energy and dollar savings; impacts on operation and maintenance (O and M); and, when applicable, a discussion of energy supply and demand, energy security, and environmental issues. A description of the evaluation methodologies and technical and cost assumptions is also provided for each ERO. Summary tables present the cost-effectiveness of energy end-use equipment before and after the implementation of each ERO and present the results of the life-cycle cost (LCC) analysis indicating the net present value (NPV) and value index (VI) of each ERO. Finally, an appendix includes a summary of an economic analysis case study of the South Vandenberg Power Plant (SVPP) operating scenarios.

  1. Location-Based Resource Allocation for OFDMA Cognitive Radio Systems

    KAUST Repository

    Ghorbel, Mahdi

    2011-05-01

    Cognitive radio is one of the hot topics for emerging and future wireless communication. It has been proposed as a suitable solution for the spectrum scarcity caused by the increase in frequency demand. The concept is based on allowing unlicensed users, called cognitive or secondary users, to share the unoccupied frequency bands with their owners, called the primary users, under constraints on the interference they cause to them. In order to estimate this interference, the cognitive system usually uses the channel state information to the primary user, which is often impractical to obtain. However, we propose to use location information, which is easier to obtain, to estimate this interference. The purpose of this work is to propose a subchannel and power allocation method which maximizes the secondary users\\' total capacity under the constraints of limited budget power and total interference to the primary under certain threshold. We model the problem as a constrained optimization problem for both downlink and uplink cases. Then, we propose low-complexity resource allocation schemes based on the waterfilling algorithm. The simulation results show the efficiency of the proposed method with comparison to the exhaustive search algorithm.

  2. A STUDY ON RANKING METHOD IN RETRIEVING WEB PAGES BASED ON CONTENT AND LINK ANALYSIS: COMBINATION OF FOURIER DOMAIN SCORING AND PAGERANK SCORING

    Directory of Open Access Journals (Sweden)

    Diana Purwitasari

    2008-01-01

    Full Text Available Ranking module is an important component of search process which sorts through relevant pages. Since collection of Web pages has additional information inherent in the hyperlink structure of the Web, it can be represented as link score and then combined with the usual information retrieval techniques of content score. In this paper we report our studies about ranking score of Web pages combined from link analysis, PageRank Scoring, and content analysis, Fourier Domain Scoring. Our experiments use collection of Web pages relate to Statistic subject from Wikipedia with objectives to check correctness and performance evaluation of combination ranking method. Evaluation of PageRank Scoring show that the highest score does not always relate to Statistic. Since the links within Wikipedia articles exists so that users are always one click away from more information on any point that has a link attached, it it possible that unrelated topics to Statistic are most likely frequently mentioned in the collection. While the combination method show link score which is given proportional weight to content score of Web pages does effect the retrieval results.

  3. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  4. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    the parameters of the model under the null hypothesis of the cointegration rank r = 1, 2, ..., p-1. This step provides consistent estimates of the cointegration degree, the cointegration vectors, the speed of adjustment to the equilibrium parameters and the common trends. In the second step we carry out a sup......-likelihood ratio test of no-cointegration on the estimated p - r common trends that are not cointegrated under the null. The cointegration degree is re-estimated in the second step to allow for new cointegration relationships with different memory. We augment the error correction model in the second step...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  5. Cointegration rank testing under conditional heteroskedasticity

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, Robert M.

    2010-01-01

    We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic......, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples under a variety of conditionally heteroskedastic innovation processes. An empirical application to the term structure of interest rates is given....

  6. Rankings, creatividad y urbanismo

    Directory of Open Access Journals (Sweden)

    JOAQUÍN SABATÉ

    2008-08-01

    Full Text Available La competencia entre ciudades constituye uno de los factores impulsores de procesos de renovación urbana y los rankings han devenido instrumentos de medida de la calidad de las ciudades. Nos detendremos en el caso de un antiguo barrio industrial hoy en vías de transformación en distrito "creativo" por medio de una intervención urbanística de gran escala. Su análisis nos descubre tres claves críticas. En primer lugar, nos obliga a plantearnos la definición de innovación urbana y cómo se integran el pasado, la identidad y la memoria en la construcción del futuro. Nos lleva a comprender que la innovación y el conocimiento no se "dan" casualmente, sino que son el fruto de una larga y compleja red en la que participan saberes, espacios, actores e instituciones diversas en naturaleza, escala y magnitud. Por último nos obliga a reflexionar sobre el valor que se le otorga a lo local en los procesos de renovación urbana.Competition among cities constitutes one ofthe main factors o furban renewal, and rankings have become instruments to indícate cities quality. Studying the transformation of an old industrial quarter into a "creative district" by the means ofa large scale urban project we highlight three main conclusions. First, itasks us to reconsider the notion ofurban innovation and hoto past, identity and memory should intégrate the future development. Second, it shows that innovation and knowledge doesn't yield per chance, but are the result ofa large and complex grid of diverse knowledges, spaces, agents and institutions. Finally itforces us to reflect about the valué attributed to the "local" in urban renewalprocesses.

  7. Simulation-based crisis resource management training for pediatric critical care medicine: a review for instructors.

    Science.gov (United States)

    Cheng, Adam; Donoghue, Aaron; Gilfoyle, Elaine; Eppich, Walter

    2012-03-01

    To review the essential elements of crisis resource management and provide a resource for instructors by describing how to use simulation-based training to teach crisis resource management principles in pediatric acute care contexts. A MEDLINE-based literature source. OUTLINE OF REVIEW: This review is divided into three main sections: Background, Principles of Crisis Resource Management, and Tools and Resources. The background section provides the brief history and definition of crisis resource management. The next section describes all the essential elements of crisis resource management, including leadership and followership, communication, teamwork, resource use, and situational awareness. This is followed by a review of evidence supporting the use of simulation-based crisis resource management training in health care. The last section provides the resources necessary to develop crisis resource management training using a simulation-based approach. This includes a description of how to design pediatric simulation scenarios, how to effectively debrief, and a list of potential assessment tools that instructors can use to evaluate crisis resource management performance during simulation-based training. Crisis resource management principles form the foundation for efficient team functioning and subsequent error reduction in high-stakes environments such as acute care pediatrics. Effective instructor training is required for those programs wishing to teach these principles using simulation-based learning. Dissemination and integration of these principles into pediatric critical care practice has the potential for a tremendous impact on patient safety and outcomes.

  8. Exploration and Description of Faith-Based Health Resources: Findings Inform Advancing Holistic Health Care.

    Science.gov (United States)

    Dyess, Susan MacLeod

    2015-01-01

    It is important to use all holistic resource opportunities in communities, such as integrative healing centers, and mind-body-spirit approaches to health. These holistic approaches may be realized through nontraditional avenues, such as faith-based resources. This article reports on an exploratory study that describes faith-based resources supporting holistic health in a southeastern region of the United States. A working definition for "faith-based health resources" was "ecumenical and interfaith community-based, open-access health resources that include in mission for service a reference to faith." Excluded from the definition were institutional services from hospitals, focused social services from area agencies, and federally funded services.

  9. Autonomic Resource Provisioning for Cloud-Based Software

    DEFF Research Database (Denmark)

    Jamshidi, Pooyan; Ahmad, Aakash; Pahl, Claus

    2014-01-01

    Elasticity endows a software system with the ability to maintain optimal user experience by automatically acquiring and releasing resources, while paying only for what they require. The mechanism for automatically adding or removing resources on the fly is referred to as auto-scaling. The state-o...

  10. Effectiveness of community-based mangrove management for sustainable resource use and livelihood support

    NARCIS (Netherlands)

    Damastuti, Ekaningrum; Groot, de Dolf

    2017-01-01

    Community-Based Mangrove Management (CBMM) is implemented with different approaches and outcomes. This study examined the effectiveness of various CBMM practices to achieve sustainable management of mangrove resources. We analyzed local mangrove resource management strategies in four coastal

  11. Social class rank, essentialism, and punitive judgment.

    Science.gov (United States)

    Kraus, Michael W; Keltner, Dacher

    2013-08-01

    Recent evidence suggests that perceptions of social class rank influence a variety of social cognitive tendencies, from patterns of causal attribution to moral judgment. In the present studies we tested the hypotheses that upper-class rank individuals would be more likely to endorse essentialist lay theories of social class categories (i.e., that social class is founded in genetically based, biological differences) than would lower-class rank individuals and that these beliefs would decrease support for restorative justice--which seeks to rehabilitate offenders, rather than punish unlawful action. Across studies, higher social class rank was associated with increased essentialism of social class categories (Studies 1, 2, and 4) and decreased support for restorative justice (Study 4). Moreover, manipulated essentialist beliefs decreased preferences for restorative justice (Study 3), and the association between social class rank and class-based essentialist theories was explained by the tendency to endorse beliefs in a just world (Study 2). Implications for how class-based essentialist beliefs potentially constrain social opportunity and mobility are discussed.

  12. Towards the Sigma Online Learning Model for crowdsourced recommendations of good web-based learning resources

    OpenAIRE

    Aaberg, Robin Garen

    2016-01-01

    The web based learning resources is believed to be playing an active role in the learning environment of higher education today. This qualitative study is exploring how students at Bergen University College incorporate web-based learning resources in their learning activities. At the core of this research is the problem of retrieving good web-resources after their first discovery. Usefull and knowledge granting web-resources are discovered within a context of topics, objectives. It is here ar...

  13. SAR-Based Wind Resource Statistics in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    Alfredo Peña

    2011-01-01

    Full Text Available Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

  14. Multirelational Social Recommendations via Multigraph Ranking.

    Science.gov (United States)

    Mao, Mingsong; Lu, Jie; Zhang, Guangquan; Zhang, Jinlong

    2017-12-01

    Recommender systems aim to identify relevant items for particular users in large-scale online applications. The historical rating data of users is a valuable input resource for many recommendation models such as collaborative filtering (CF), but these models are known to suffer from the rating sparsity problem when the users or items under consideration have insufficient rating records. With the continued growth of online social networks, the increased user-to-user relationships are reported to be helpful and can alleviate the CF rating sparsity problem. Although researchers have developed a range of social network-based recommender systems, there is no unified model to handle multirelational social networks. To address this challenge, this paper represents different user relationships in a multigraph and develops a multigraph ranking model to identify and recommend the nearest neighbors of particular users in high-order environments. We conduct empirical experiments on two real-world datasets: 1) Epinions and 2) Last.fm, and the comprehensive comparison with other approaches demonstrates that our model improves recommendation performance in terms of both recommendation coverage and accuracy, especially when the rating data are sparse.

  15. Ranking health between countries in international comparisons

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    2014-01-01

    Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions and docum......Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions...

  16. Low-rank coal research

    Energy Technology Data Exchange (ETDEWEB)

    Weber, G. F.; Laudal, D. L.

    1989-01-01

    This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

  17. Wikipedia ranking of world universities

    Science.gov (United States)

    Lages, José; Patt, Antoine; Shepelyansky, Dima L.

    2016-03-01

    We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

  18. Assessing the Readability of Medical Documents: A Ranking Approach.

    Science.gov (United States)

    Zheng, Jiaping; Yu, Hong

    2018-03-23

    The use of electronic health record (EHR) systems with patient engagement capabilities, including viewing, downloading, and transmitting health information, has recently grown tremendously. However, using these resources to engage patients in managing their own health remains challenging due to the complex and technical nature of the EHR narratives. Our objective was to develop a machine learning-based system to assess readability levels of complex documents such as EHR notes. We collected difficulty ratings of EHR notes and Wikipedia articles using crowdsourcing from 90 readers. We built a supervised model to assess readability based on relative orders of text difficulty using both surface text features and word embeddings. We evaluated system performance using the Kendall coefficient of concordance against human ratings. Our system achieved significantly higher concordance (.734) with human annotators than did a baseline using the Flesch-Kincaid Grade Level, a widely adopted readability formula (.531). The improvement was also consistent across different disease topics. This method's concordance with an individual human user's ratings was also higher than the concordance between different human annotators (.658). We explored methods to automatically assess the readability levels of clinical narratives. Our ranking-based system using simple textual features and easy-to-learn word embeddings outperformed a widely used readability formula. Our ranking-based method can predict relative difficulties of medical documents. It is not constrained to a predefined set of readability levels, a common design in many machine learning-based systems. Furthermore, the feature set does not rely on complex processing of the documents. One potential application of our readability ranking is personalization, allowing patients to better accommodate their own background knowledge. ©Jiaping Zheng, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.03.2018.

  19. Een resource-based portfoliobenadering : strategieën op basis van de resource-based view

    NARCIS (Netherlands)

    Santema, S.C.; Rijt, van de J.

    1999-01-01

    In dit artikel wordt met behulp van de Resourcebased View (RBV) een portfoliomodel voor resources ontwikkeld. De RBV kenmerkt zich tot op heden als een theorie met een eenzijdige focus op sterke, niet-imiteerbare, immobiele resources. In dit artikel wordt weergegeven hoe een onderneming kan omgaan

  20. Extreme learning machine for ranking: generalization analysis and applications.

    Science.gov (United States)

    Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin

    2014-05-01

    The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Statistical methods for ranking data

    CERN Document Server

    Alvo, Mayer

    2014-01-01

    This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

  2. Research on Green Manufacturing Innovation Based on Resource Environment Protection

    Science.gov (United States)

    Jie, Xu

    2017-11-01

    Green manufacturing is a trend of manufacturing industry in the future, and is of great significance to resource protection and environmental protection. This paper first studies the green manufacturing innovation system, and then decomposes the green manufacturing innovation dimensions, and constructs the green manufacturing innovation dimension space. Finally, from the view of resource protection and environmental protection, this paper explores the path of green manufacturing innovation.

  3. Agro-tourism and ranking

    Science.gov (United States)

    Cioca, L. I.; Giurea, R.; Precazzini, I.; Ragazzi, M.; Achim, M. I.; Schiavon, M.; Rada, E. C.

    2018-05-01

    Nowadays the global tourism growth has caused a significant interest in research focused on the impact of the tourism on environment and community. The purpose of this study is to introduce a new ranking for the classification of tourist accommodation establishments with the functions of agro-tourism boarding house type by examining the sector of agro-tourism based on a research aimed to improve the economic, socio-cultural and environmental performance of agrotourism structures. This paper links the criteria for the classification of agro-tourism boarding houses (ABHs) to the impact of agro-tourism activities on the environment, enhancing an eco-friendly approach on agro-tourism activities by increasing the quality reputation of the agro-tourism products and services. Taking into account the impact on the environment, agrotourism can play an important role by protecting and conserving it.

  4. A resource-based theory of market structure and organizational form

    NARCIS (Netherlands)

    van Witteloostuijn, A.; Boone, C.A.J.J.

    We argue that combining the insights from both the industrial organization and organizational ecology perspectives is likely to produce value added. We develop a resource-based theory of market structure, where resources pertain to the environmental assets (together forming the resource space)

  5. A URI-based approach for addressing fragments of media resources on the Web

    NARCIS (Netherlands)

    E. Mannens; D. van Deursen; R. Troncy (Raphael); S. Pfeiffer; C. Parker (Conrad); Y. Lafon; A.J. Jansen (Jack); M. Hausenblas; R. van de Walle

    2011-01-01

    htmlabstractTo make media resources a prime citizen on the Web, we have to go beyond simply replicating digital media files. The Web is based on hyperlinks between Web resources, and that includes hyperlinking out of resources (e.g., from a word or an image within a Web page) as well as hyperlinking

  6. Diversity rankings among bacterial lineages in soil.

    Science.gov (United States)

    Youssef, Noha H; Elshahed, Mostafa S

    2009-03-01

    We used rarefaction curve analysis and diversity ordering-based approaches to rank the 11 most frequently encountered bacterial lineages in soil according to diversity in 5 previously reported 16S rRNA gene clone libraries derived from agricultural, undisturbed tall grass prairie and forest soils (n=26,140, 28 328, 31 818, 13 001 and 53 533). The Planctomycetes, Firmicutes and the delta-Proteobacteria were consistently ranked among the most diverse lineages in all data sets, whereas the Verrucomicrobia, Gemmatimonadetes and beta-Proteobacteria were consistently ranked among the least diverse. On the other hand, the rankings of alpha-Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes and Chloroflexi varied widely in different soil clone libraries. In general, lineages exhibiting largest differences in diversity rankings also exhibited the largest difference in relative abundance in the data sets examined. Within these lineages, a positive correlation between relative abundance and diversity was observed within the Acidobacteria, Actinobacteria and Chloroflexi, and a negative diversity-abundance correlation was observed within the Bacteroidetes. The ecological and evolutionary implications of these results are discussed.

  7. Wide-Area Publish/Subscribe Mobile Resource Discovery Based on IPv6 GeoNetworking

    OpenAIRE

    Noguchi, Satoru; Matsuura, Satoshi; Inomata, Atsuo; Fujikawa, Kazutoshi; Sunahara, Hideki

    2013-01-01

    Resource discovery is an essential function for distributed mobile applications integrated in vehicular communication systems. Key requirements of the mobile resource discovery are wide-area geographic-based discovery and scalable resource discovery not only inside a vehicular ad-hoc network but also through the Internet. While a number of resource discovery solutions have been proposed, most of them have focused on specific scale of network. Furthermore, managing a large number of mobile res...

  8. Profit-based conventional resource scheduling with renewable energy penetration

    Science.gov (United States)

    Reddy, K. Srikanth; Panwar, Lokesh Kumar; Kumar, Rajesh; Panigrahi, B. K.

    2017-08-01

    Technological breakthroughs in renewable energy technologies (RETs) enabled them to attain grid parity thereby making them potential contenders for existing conventional resources. To examine the market participation of RETs, this paper formulates a scheduling problem accommodating energy market participation of wind- and solar-independent power producers (IPPs) treating both conventional and RETs as identical entities. Furthermore, constraints pertaining to penetration and curtailments of RETs are restructured. Additionally, an appropriate objective function for profit incurred by conventional resource IPPs through reserve market participation as a function of renewable energy curtailment is also proposed. The proposed concept is simulated with a test system comprising 10 conventional generation units in conjunction with solar photovoltaic (SPV) and wind energy generators (WEG). The simulation results indicate that renewable energy integration and its curtailment limits influence the market participation or scheduling strategies of conventional resources in both energy and reserve markets. Furthermore, load and reliability parameters are also affected.

  9. Basic framework of urban design based on natural resources

    Science.gov (United States)

    Lubis, Irwar; Nasution, Mahyuddin K. M.; Maulina, Maudy

    2018-03-01

    To establishment of the city always begins because the availability of natural resources that meet the basic needs of its inhabitants, but after that the city relies on the sustainability of those basic need, which is primarily dependent on transportation. Transportation becomes the main needs of the city. Transportation, however, results in the potential for the city’s discomfort with noise and pollution, which mixes with the frenetic city life. Therefore, this paper reveals a basic framework using natural resources to reduce the noise and the pollution.

  10. Ranking beta sheet topologies of proteins

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2010-01-01

    One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all beta-topologies (partitions of beta-strands into sheets, orderings of strands within sheets and orientations...... of paired strands) of a given protein. We show that the beta-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many beta-strands. The results reported...... in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked beta-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly...

  11. Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC-MS/MS

    Science.gov (United States)

    Bilbao, Aivett; Zhang, Ying; Varesio, Emmanuel; Luban, Jeremy; Strambio-De-Castillia, Caterina; Lisacek, Frédérique; Hopfgartner, Gérard

    2016-01-01

    Data-independent acquisition LC-MS/MS techniques complement supervised methods for peptide quantification. However, due to the wide precursor isolation windows, these techniques are prone to interference at the fragment ion level, which in turn is detrimental for accurate quantification. The “non-outlier fragment ion” (NOFI) ranking algorithm has been developed to assign low priority to fragment ions affected by interference. By using the optimal subset of high priority fragment ions these interfered fragment ions are effectively excluded from quantification. NOFI represents each fragment ion as a vector of four dimensions related to chromatographic and MS fragmentation attributes and applies multivariate outlier detection techniques. Benchmarking conducted on a well-defined quantitative dataset (i.e. the SWATH Gold Standard), indicates that NOFI on average is able to accurately quantify 11-25% more peptides than the commonly used Top-N library intensity ranking method. The sum of the area of the Top3-5 NOFIs produces similar coefficients of variation as compared to the library intensity method but with more accurate quantification results. On a biologically relevant human dendritic cell digest dataset, NOFI properly assigns low priority ranks to 85% of annotated interferences, resulting in sensitivity values between 0.92 and 0.80 against 0.76 for the Spectronaut interference detection algorithm. PMID:26412574

  12. Ranked solutions to a class of combinatorial optimizations—with applications in mass spectrometry based peptide sequencing and a variant of directed paths in random media

    Science.gov (United States)

    Doerr, Timothy P.; Alves, Gelio; Yu, Yi-Kuo

    2005-08-01

    Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time using the transfer matrix technique or, equivalently, the dynamic programming approach. This suggests a way to efficiently find approximate solutions-find a transformation that makes the cost function as similar as possible to that of the solvable class. After keeping many high-ranking solutions using the approximate cost function, one may then re-assess these solutions with the full cost function to find the best approximate solution. Under this approach, it is important to be able to assess the quality of the solutions obtained, e.g., by finding the true ranking of the kth best approximate solution when all possible solutions are considered exhaustively. To tackle this statistical issue, we provide a systematic method starting with a scaling function generated from the finite number of high-ranking solutions followed by a convergent iterative mapping. This method, useful in a variant of the directed paths in random media problem proposed here, can also provide a statistical significance assessment for one of the most important proteomic tasks-peptide sequencing using tandem mass spectrometry data. For directed paths in random media, the scaling function depends on the particular realization of randomness; in the mass spectrometry case, the scaling function is spectrum-specific.

  13. Resource recovery from bio-based production processes: a future necessity?

    DEFF Research Database (Denmark)

    Mansouri, Seyed Soheil; S.B.A. Udugama, Isuru; Cignitti, Stefano

    2017-01-01

    The promise of transforming waste streams with small economic value into valuable products makes resource recovery technologies in bio-based production processes an attractive proposition. However, the use of resource recovery technologies in industrial applications is still minimal, despite its...... technologies to industrial bio-based production processes. The role and importance of economics, technology readiness and socio-environmental impacts of resource recovery in successfully implementing resource recovery technologies in industrial bio-based production processes is also discussed. Finally, based...... wide use in closely related processes such as dairy production. In this paper, a perspective on the role of resource recovery in bio-based production processes is provided through reviewing the past practice and identifying the benefits, opportunities and challenges of introducing resource recovery...

  14. Co-integration Rank Testing under Conditional Heteroskedasticity

    DEFF Research Database (Denmark)

    Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

    null distributions of the rank statistics coincide with those derived by previous authors who assume either i.i.d. or (strict and covariance) stationary martingale difference innovations. We then propose wild bootstrap implementations of the co-integrating rank tests and demonstrate that the associated...... bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show the same is also true of the corresponding rank tests based on the i.i.d. bootstrap of Swensen (2006). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap......, it preserves in the re-sampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence sug- gests that, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples un...

  15. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

  16. A framework for automatic information quality ranking of diabetes websites.

    Science.gov (United States)

    Belen Sağlam, Rahime; Taskaya Temizel, Tugba

    2015-01-01

    Objective: When searching for particular medical information on the internet the challenge lies in distinguishing the websites that are relevant to the topic, and contain accurate information. In this article, we propose a framework that automatically identifies and ranks diabetes websites according to their relevance and information quality based on the website content. Design: The proposed framework ranks diabetes websites according to their content quality, relevance and evidence based medicine. The framework combines information retrieval techniques with a lexical resource based on Sentiwordnet making it possible to work with biased and untrusted websites while, at the same time, ensuring the content relevance. Measurement: The evaluation measurements used were Pearson-correlation, true positives, false positives and accuracy. We tested the framework with a benchmark data set consisting of 55 websites with varying degrees of information quality problems. Results: The proposed framework gives good results that are comparable with the non-automated information quality measuring approaches in the literature. The correlation between the results of the proposed automated framework and ground-truth is 0.68 on an average with p < 0.001 which is greater than the other proposed automated methods in the literature (r score in average is 0.33).

  17. Rank reduction of correlation matrices by majorization

    NARCIS (Netherlands)

    R. Pietersz (Raoul); P.J.F. Groenen (Patrick)

    2004-01-01

    textabstractIn this paper a novel method is developed for the problem of finding a low-rank correlation matrix nearest to a given correlation matrix. The method is based on majorization and therefore it is globally convergent. The method is computationally efficient, is straightforward to implement,

  18. A generalization of Friedman's rank statistic

    NARCIS (Netherlands)

    Kroon, de J.; Laan, van der P.

    1983-01-01

    In this paper a very natural generalization of the two·way analysis of variance rank statistic of FRIEDMAN is given. The general distribution-free test procedure based on this statistic for the effect of J treatments in a random block design can be applied in general two-way layouts without

  19. An R package for analyzing and modeling ranking data.

    Science.gov (United States)

    Lee, Paul H; Yu, Philip L H

    2013-05-14

    In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought

  20. Face the hierarchy: ERP and oscillatory brain responses in social rank processing.

    Science.gov (United States)

    Breton, Audrey; Jerbi, Karim; Henaff, Marie-Anne; Cheylus, Anne; Baudouin, Jean-Yves; Schmitz, Christina; Krolak-Salmon, Pierre; Van der Henst, Jean-Baptiste

    2014-01-01

    Recognition of social hierarchy is a key feature that helps us navigate through our complex social environment. Neuroimaging studies have identified brain structures involved in the processing of hierarchical stimuli but the precise temporal dynamics of brain activity associated with such processing remains largely unknown. Here, we used electroencephalography to examine the effect of social hierarchy on neural responses elicited by faces. In contrast to previous studies, the key manipulation was that a hierarchical context was constructed, not by varying facial expressions, but by presenting neutral-expression faces in a game setting. Once the performance-based hierarchy was established, participants were presented with high-rank, middle-rank and low-rank player faces and had to evaluate the rank of each face with respect to their own position. Both event-related potentials and task-related oscillatory activity were investigated. Three main findings emerge from the study. First, the experimental manipulation had no effect on the early N170 component, which may suggest that hierarchy did not modulate the structural encoding of neutral-expression faces. Second, hierarchy significantly modulated the amplitude of the late positive potential (LPP) within a 400-700 ms time-window, with more a prominent LPP occurring when the participants processed the face of the highest-rank player. Third, high-rank faces were associated with the highest reduction of alpha power. Taken together these findings provide novel electrophysiological evidence for enhanced allocation of attentional resource in the presence of high-rank faces. At a broader level, this study brings new insights into the neural processing underlying social categorization.

  1. Perceived Family Resources Based on Number of Members with ADHD

    Science.gov (United States)

    Corwin, Melinda; Mulsow, Miriam; Feng, Du

    2012-01-01

    Objective: This study examines how the number of family members with ADHD affects other family members' perceived resources. Method: A total of 40 adolescents diagnosed with ADHD and their mothers, fathers, and adolescent siblings living in the household participated. Hierarchical linear modeling was used to analyze family-level data from a total…

  2. Human Resources Administration: A School-Based Perspective. Fourth Edition

    Science.gov (United States)

    Smith, Richard

    2009-01-01

    Enhanced and updated, this Fourth Edition of Richard E. Smith's highly successful text examines the growing role of the principal in planning, hiring, staff development, supervision, and other human resource functions. The Fourth Edition includes new sections on ethics, induction, and the role of the mentor teacher. This edition also introduces…

  3. Utilization of Web-Based Information Resources for Researchers in ...

    African Journals Online (AJOL)

    All the postgraduate students and lectures of three universities in the state who are registered library users formed the population of the study. Two research ... The implication of the findings implies that university libraries that provide such resources effectively will help to promote academic scholarship and research.

  4. A cross-benchmark comparison of 87 learning to rank methods

    NARCIS (Netherlands)

    Tax, N.; Bockting, S.; Hiemstra, D.

    2015-01-01

    Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. New learning to rank methods are generally evaluated on benchmark test collections. However, comparison of learning to rank methods based on evaluation results is hindered

  5. Economic transition policies in Chinese resource-based cities: An overview of government efforts

    International Nuclear Information System (INIS)

    Li, Huijuan; Long, Ruyin; Chen, Hong

    2013-01-01

    Resource-based cities in China have made momentous contributions to the development of the national economy for decades. However, with the depletion of natural resources, their sustainable development is challenging and transition is important. The Chinese government has made great efforts to help resource-based cities. The purpose of this study is to investigate transition policies and their implementation. Firstly, we reviewed previous studies and summarized the essential elements of some successful resource-based cities, which are useful experiences for Chinese resource-based cities. Secondly, we studied the development of resource-based cities over the past 10 years with a focus on economic development, industrial structure, government revenue and environmental conditions. We found that resource-based cities were less developed compared to other cities. The main reasons are the after-effects of a planned economy, an unreasonable tax system, planning mistakes and misguided resources exploitation policies. Thirdly, we analyzed several aspects of the policy responses after the introduction of transition policies, including designating 69 resource-exhausted cities, supporting cities with funds and projects, formulating transition plans and evaluating transition performance. However, there are some deficiencies in the process of policy implementation. Finally, some recommendations were provided to improve transition performance and sustainable development for resource-based cities. - Highlights: ► Analyze the development of Chinese resource-based cities from four aspects. ► Analyze the causes of less development in resource-based cities. ► Investigate policies and their responses to transformation. ► Provide recommendations to improve transformation performance and sustainable development

  6. A resource-based view of partnership strategies in health care organizations.

    Science.gov (United States)

    Yarbrough, Amy K; Powers, Thomas L

    2006-01-01

    The distribution of management structures in health care has been shifting from independent ownership to interorganizational relationships with other firms. A shortage of resources has been cited as one cause for such collaboration among health care entities. The resource- based view of the firm suggests that organizations differentiate between strategic alliances and acquisition strategies based on a firm's internal resources and the types of resources a potential partner organization possesses. This paper provides a review of the literature using the resource-based theory of the firm to understand what conditions foster different types of health care partnerships. A model of partnership alliances using the resource-based view is presented, strategic linkages are presented, managerial implications are outlined, and directions for future research are given.

  7. A multi-group and preemptable scheduling of cloud resource based on HTCondor

    Science.gov (United States)

    Jiang, Xiaowei; Zou, Jiaheng; Cheng, Yaodong; Shi, Jingyan

    2017-10-01

    Due to the features of virtual machine-flexibility, easy controlling and various system environments, more and more fields utilize the virtualization technology to construct the distributed system with the virtual resources, also including high energy physics. This paper introduce a method used in high energy physics that supports multiple resource group and preemptable cloud resource scheduling, combining virtual machine with HTCondor (a batch system). It makes resource controlling more flexible and more efficient and makes resource scheduling independent of job scheduling. Firstly, the resources belong to different experiment-groups, and the type of user-groups mapping to resource-groups(same as experiment-group) is one-to-one or many-to-one. In order to make the confused group simply to be managed, we designed the permission controlling component to ensure that the different resource-groups can get the suitable jobs. Secondly, for the purpose of elastically allocating resources for suitable resource-group, it is necessary to schedule resources like scheduling jobs. So this paper designs the cloud resource scheduling to maintain a resource queue and allocate an appropriate amount of virtual resources to the request resource-group. Thirdly, in some kind of situations, because of the resource occupied for a long time, resources need to be preempted. This paper adds the preemption function for the resource scheduling that implement resource preemption based on the group priority. Additionally, the way to preempting is soft that when virtual resources are preempted, jobs will not be killed but also be held and rematched later. It is implemented with the help of HTCondor, storing the held job information in scheduler, releasing the job to idle status and doing second matcher. In IHEP (institute of high energy physics), we have built a batch system based on HTCondor with a virtual resources pool based on Openstack. And this paper will show some cases of experiment JUNO

  8. A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

    Directory of Open Access Journals (Sweden)

    Zhijia Chen

    2015-01-01

    Full Text Available The resources in cloud environment have features such as large-scale, diversity, and heterogeneity. Moreover, the user requirements for cloud computing resources are commonly characterized by uncertainty and imprecision. Hereby, to improve the quality of cloud computing service, not merely should the traditional standards such as cost and bandwidth be satisfied, but also particular emphasis should be laid on some extended standards such as system friendliness. This paper proposes a dynamic resource scheduling method based on fuzzy control theory. Firstly, the resource requirements prediction model is established. Then the relationships between resource availability and the resource requirements are concluded. Afterwards fuzzy control theory is adopted to realize a friendly match between user needs and resources availability. Results show that this approach improves the resources scheduling efficiency and the quality of service (QoS of cloud computing.

  9. Texture Repairing by Unified Low Rank Optimization

    Institute of Scientific and Technical Information of China (English)

    Xiao Liang; Xiang Ren; Zhengdong Zhang; Yi Ma

    2016-01-01

    In this paper, we show how to harness both low-rank and sparse structures in regular or near-regular textures for image completion. Our method is based on a unified formulation for both random and contiguous corruption. In addition to the low rank property of texture, the algorithm also uses the sparse assumption of the natural image: because the natural image is piecewise smooth, it is sparse in certain transformed domain (such as Fourier or wavelet transform). We combine low-rank and sparsity properties of the texture image together in the proposed algorithm. Our algorithm based on convex optimization can automatically and correctly repair the global structure of a corrupted texture, even without precise information about the regions to be completed. This algorithm integrates texture rectification and repairing into one optimization problem. Through extensive simulations, we show our method can complete and repair textures corrupted by errors with both random and contiguous supports better than existing low-rank matrix recovery methods. Our method demonstrates significant advantage over local patch based texture synthesis techniques in dealing with large corruption, non-uniform texture, and large perspective deformation.

  10. A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

    Directory of Open Access Journals (Sweden)

    Xuejun Li

    2016-01-01

    Full Text Available Market-oriented reverse auction is an efficient and cost-effective method for resource allocation in cloud workflow systems since it can dynamically allocate resources depending on the supply-demand relationship of the cloud market. However, during the auction the price of cloud resource is usually fixed, and the current resource allocation mechanisms cannot adapt to the changeable market properly which results in the low efficiency of resource utilization. To address such a problem, a dynamic pricing reverse auction-based resource allocation mechanism is proposed. During the auction, resource providers can change prices according to the trading situation so that our novel mechanism can increase the chances of making a deal and improve efficiency of resource utilization. In addition, resource providers can improve their competitiveness in the market by lowering prices, and thus users can obtain cheaper resources in shorter time which would decrease monetary cost and completion time for workflow execution. Experiments with different situations and problem sizes are conducted for dynamic pricing-based allocation mechanism (DPAM on resource utilization and the measurement of Time⁎Cost (TC. The results show that our DPAM can outperform its representative in resource utilization, monetary cost, and completion time and also obtain the optimal price reduction rates.

  11. Quality indicators in the mobile industry rankings based on indicators of customer satisfaction with the hybrid approach DEMATEL and ANP appropriate strategy based on gray system

    Directory of Open Access Journals (Sweden)

    Ashouri Fatemeh

    2016-01-01

    Full Text Available The quality of services as a vital element in the strategic competitiveness and commercial success are various methods have been developed to evaluate it. Prioritizing qualitative indicators based on the quality of mobile phone services enables the company gives top priority due to the higher percentage of satisfied customers provide. This study tries to customer satisfaction according to criteria to prioritize mobile operators pay qualitative characteristics. A sample consisted of 450 individuals (46% women, 54% men from IRANCELL operator (Iran in 2015 which selected randomly. Results shows between four considered strategies maximum priorities belong to S1 which is denote to more services beyond customer expectations.

  12. Colorado's hydrothermal resource base: an assessment

    Energy Technology Data Exchange (ETDEWEB)

    Pearl, R.H.

    1981-01-01

    As part of its effort to more accurately describe the nations geothrmal resource potential, the US Department of Energy/Division of Geothermal Energy contracted with the Colorado Geological survey to appraise the hydrothermal (hot water) geothermal resources of Colorado. Part of this effort required that the amount of energy that could possibly be contained in the various hydrothermal systems in Colorado be estimated. The findings of that assessment are presented. To make these estimates the geothermometer reservoir temperatures estimated by Barrett and Pearl (1978) were used. In addition, the possible reservoir size and extent were estimated and used. This assessment shows that the total energy content of the thermal systems in Colorado could range from 4.872 x 10{sup 15} BTU's to 13.2386 x 10{sup 15} BTU's.

  13. Sign rank versus Vapnik-Chervonenkis dimension

    Science.gov (United States)

    Alon, N.; Moran, Sh; Yehudayoff, A.

    2017-12-01

    This work studies the maximum possible sign rank of sign (N × N)-matrices with a given Vapnik-Chervonenkis dimension d. For d=1, this maximum is three. For d=2, this maximum is \\widetilde{\\Theta}(N1/2). For d >2, similar but slightly less accurate statements hold. The lower bounds improve on previous ones by Ben-David et al., and the upper bounds are novel. The lower bounds are obtained by probabilistic constructions, using a theorem of Warren in real algebraic topology. The upper bounds are obtained using a result of Welzl about spanning trees with low stabbing number, and using the moment curve. The upper bound technique is also used to: (i) provide estimates on the number of classes of a given Vapnik-Chervonenkis dimension, and the number of maximum classes of a given Vapnik-Chervonenkis dimension--answering a question of Frankl from 1989, and (ii) design an efficient algorithm that provides an O(N/log(N)) multiplicative approximation for the sign rank. We also observe a general connection between sign rank and spectral gaps which is based on Forster's argument. Consider the adjacency (N × N)-matrix of a Δ-regular graph with a second eigenvalue of absolute value λ and Δ ≤ N/2. We show that the sign rank of the signed version of this matrix is at least Δ/λ. We use this connection to prove the existence of a maximum class C\\subseteq\\{+/- 1\\}^N with Vapnik-Chervonenkis dimension 2 and sign rank \\widetilde{\\Theta}(N1/2). This answers a question of Ben-David et al. regarding the sign rank of large Vapnik-Chervonenkis classes. We also describe limitations of this approach, in the spirit of the Alon-Boppana theorem. We further describe connections to communication complexity, geometry, learning theory, and combinatorics. Bibliography: 69 titles.

  14. Commercial and Industrial Base Intermittent Resource Management Pilot

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Sporborg, Pamela; Sheik, Imran; Huffaker, Erich; Piette, Mary Ann

    2010-11-30

    This scoping study summarizes the challenges with integrating wind and solar generation into the California's electricity grid. These challenges include: Smoothing intra-hour variability; - Absorbing excess renewable energy during over-generation periods; - Addressing morning and evening ramping periods. In addition, there are technical challenges to integrating retail demand response (DR) triggered by the wholesale conditions into the CAISO markets. The study describes the DR programs available to the consumers through the utilities in California and CAISO's ancillary services market because an integration of the wholesale and retail DR requires an understanding of these different offerings and the costs associated with acquiring them. Demand-side active and passive storage systems are proposed as technologies that may be used to mitigate the effects of intermittence due to renewable generation. Commercial building technologies as well as industrial facilities with storage capability are identified as targets for the field tests. Two systems used for ancillary services communications are identified as providing the triggers for DR enablement. Through the field tests, issues related to communication, automation and flexibility of demand-side resources will be explored and the performance of technologies that participate in the field tests will be evaluated. The major outcome of this research is identifying and defining flexibility of DR resources and optimized use of these resources to respond to grid conditions.

  15. Teleportation is necessary for faithful quantum state transfer through noisy channels of maximal rank

    International Nuclear Information System (INIS)

    Romano, Raffaele; Loock, Peter van

    2010-01-01

    Quantum teleportation enables deterministic and faithful transmission of quantum states, provided a maximally entangled state is preshared between sender and receiver, and a one-way classical channel is available. Here, we prove that these resources are not only sufficient, but also necessary, for deterministically and faithfully sending quantum states through any fixed noisy channel of maximal rank, when a single use of the cannel is admitted. In other words, for this family of channels, there are no other protocols, based on different (and possibly cheaper) sets of resources, capable of replacing quantum teleportation.

  16. Research notes and commentaries managing knowledge in foreign entry strategies: A resource-based analysis

    NARCIS (Netherlands)

    K.E. Meyer (Klaus); D.M. Wright (Mike); S. Pruthi (Sarika)

    2009-01-01

    textabstractInternational strategies vary in their potential to exploit and augment a firm's resources, especially its knowledge base. Resource-based analysis suggests clustering the diverse entry modes in terms of their exploitation and augmentation characteristics. We thus introduce a new

  17. More explicit communication after classroom-based crew resource management training: results of a pragmatic trial.

    NARCIS (Netherlands)

    Verbeek-van Noord, I.; Bruijne, M.C. de; Twisk, J.W.R.; Dyck, C. van; Wagner, C.

    2015-01-01

    Rationale, aims and objectives: Aviation-based crew resource management trainings to optimize non-technical skills among professionals are often suggested for health care as a way to increase patient safety. Our aim was to evaluate the effect of a 2-day classroom-based crew resource management (CRM)

  18. More explicit communication after classroom-based crew resource management training: results of a pragmatic trial

    NARCIS (Netherlands)

    van Noord, I.; de Bruijne, M.C.; Twisk, J.W.R.; van Dyck, C.; Wagner, C.

    2015-01-01

    Rationale, aims and objectives Aviation-based crew resource management trainings to optimize non-technical skills among professionals are often suggested for health care as a way to increase patient safety. Our aim was to evaluate the effect of a 2-day classroom-based crew resource management (CRM)

  19. Smokes and obscurants: A health and environmental effects data base assessment: A first-order, environmental screening and ranking of Army smokes and obscurants: Phase 1 report

    Energy Technology Data Exchange (ETDEWEB)

    Shinn, J.H.; Martins, S.A.; Cederwall, P.L.; Gratt, L.B.

    1985-03-01

    An initial environmental screening and ranking is provided for each Army smoke and obscurant (S and O) depending on smoke type and smoke-generating device. This was done according to the magnitude of the impact area, the characteristic environmental concentration, the relative inhalation toxicity, the relative toxicity when ingested by animals, the aquatic toxicity, the environmental mobility when freshly deposited, and the ultimate mobility and fate in the environment. The major smoke types considered were various forms of white phosphorus (WP), red phosphorus (RP), hexachloroethane-derived smokes (HC), fog oil (SGF-2), diesel fuel smokes (DF), and some infrared obscuring agents (IR).

  20. Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

    Science.gov (United States)

    Gerner, Nadine V; Cailleaud, Kevin; Bassères, Anne; Liess, Matthias; Beketov, Mikhail A

    2017-11-01

    Hydrocarbons have an utmost economical importance but may also cause substantial ecological impacts due to accidents or inadequate transportation and use. Currently, freshwater biomonitoring methods lack an indicator that can unequivocally reflect the impacts caused by hydrocarbons while being independent from effects of other stressors. The aim of the present study was to develop a sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants, which can be used in hydrocarbon-specific bioindicators. We employed the Relative Sensitivity method and developed the sensitivity ranking S hydrocarbons based on literature ecotoxicological data supplemented with rapid and mesocosm test results. A first validation of the sensitivity ranking based on an earlier field study has been conducted and revealed the S hydrocarbons ranking to be promising for application in sensitivity based indicators. Thus, the first results indicate that the ranking can serve as the core component of future hydrocarbon-specific and sensitivity trait based bioindicators.